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Emerging Trends in Blockchain Technology and Applications: A Review and Outlook

March 2022
Journal of King Saud University - Computer and Information Sciences 34(9):6719-6742

DOI:10.1016/j.jksuci.2022.03.007

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CC BY-NC-ND 4.0

Authors:

Ahmed G. Gad

UNSW Sydney

Diana Mosa

Kafr El-Sheikh University

Laith Abualigah

Al al-Bayt University

Amr A. Abohany

Kafr El-Sheikh University

At present times, Blockchain technology is gaining more attraction with every passing day, as it has revolutionized the traditional trade due to its distributed ledger feature, every record in this ledger is secured by rules of cryptography which makes it more secure and tamper-free. This naturally led to the emergence of various types of cryptocurrency, such as Bitcoin, which builds on a technology commonly known as Blockchain. The rapid evolution of research on Blockchain calls for more research studies for investigating and analyzing the current knowledge in this field through a systematic technical study that shows the impact and significance of the related literature since the inception of the technology in 2013. From this point, in this paper, a state-of-the-art review is conducted on the most influential articles, conference papers, and review papers related to Blockchain published from 2013 to 2020 and indexed by the Web of Science Core Collection™ (WoS) world’s literature database. To attain the desired objective, after presenting an inevitable, brief overview of Blockchain technology, the collected papers have closely been analyzed along seven key research questions. Subsequently, vital valuable findings, such as the top 10 influential papers, yearly publications and citation trends, the favorite publication venues, the hottest research areas, and the most supportive funding bodies are reported, which may offer several implications about the status quo and emerging trends and frontiers of Blockchain, to guide towards establishing a baseline for both fresh and experienced researchers and practitioners before initiating a future research project on Blockchain. Furthermore, a rigorous discussion is provided on Blockchain application in diversified domains, along with different versatile use cases. Lastly, a brief insight is presented into open challenges and potential future advancements in the field of Blockchain. Summing up, this paper is meant to assist newbies in exploring and designing new Blockchain solutions, bearing in mind existing demands and challenges.

Structure of a Blockchain consisting of a sequence of blocks.

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Working nature of Blockchain.

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Types of Blockchain networks.

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Publication trends for each topic per year.

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Number of Blockchain papers yearly published and indexed by WoS.

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Content uploaded by Ahmed G. Gad

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Emerging Trends in Blockchain Technology and Applications: A Review

and Outlook

Ahmed G. Gad

⇑

, Diana T. Mosa

, Laith Abualigah

b,c

, Amr A. Abohany

Faculty of Computers and Information, Kafrelsheikh University, Kafrelsheikh, Egypt

Faculty of Computer Sciences and Informatics, Amman Arab University, 11953 Amman, Jordan

School of Computer Sciences, Universiti Sains Malaysia, Pulau Pinang 11800, Malaysia

article info

Article history:

Received 19 July 2021

Revised 24 January 2022

Accepted 5 March 2022

Available online 16 March 2022

Keywords:

Blockchain

Cryptocurrency

Consensus

Systematic review

Web of Science (WoS)

Funding agencies

Blockchain applications

Open challenges

Future directions

abstract

At present times, Blockchain technology is gaining more attraction with every passing day, as it has rev-

olutionized the traditional trade due to its distributed ledger feature, every record in this ledger is

secured by rules of cryptography which makes it more secure and tamper-free. This naturally led to

the emergence of various types of cryptocurrency, such as Bitcoin, which builds on a technology com-

monly known as Blockchain. The rapid evolution of research on Blockchain calls for more research studies

for investigating and analyzing the current knowledge in this ﬁeld through a systematic technical study

that shows the impact and signiﬁcance of the related literature since the inception of the technology in

2013. From this point, in this paper, a state-of-the-art review is conducted on the most inﬂuential articles,

conference papers, and review papers related to Blockchain published from 2013 to 2020 and indexed by

the Web of Science Core Collection

(WoS) world’s literature database. To attain the desired objective,

after presenting an inevitable, brief overview of Blockchain technology, the collected papers have closely

been analyzed along seven key research questions. Subsequently, vital valuable ﬁndings, such as the top

10 inﬂuential papers, yearly publications and citation trends, the favorite publication venues, the hottest

research areas, and the most supportive funding bodies are reported, which may offer several implica-

tions about the status quo and emerging trends and frontiers of Blockchain, to guide towards establishing

a baseline for both fresh and experienced researchers and practitioners before initiating a future research

project on Blockchain. Furthermore, a rigorous discussion is provided on Blockchain application in diver-

siﬁed domains, along with different versatile use cases. Lastly, a brief insight is presented into open chal-

lenges and potential future advancements in the ﬁeld of Blockchain. Summing up, this paper is meant to

assist newbies in exploring and designing new Blockchain solutions, bearing in mind existing demands

and challenges.

Ó2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University. This is an open access

article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Contents

1. Introduction . . . ..................................................................................................... 6720

2. Blockchain overview . . . . . . . . . . . . . . . .................................................................................. 6722

2.1. The structure of Blockchain . . . . . . . . . . . . . . .......................... .............................................. 6722

2.2. How Blockchain works? . ................................... ..................................................... 6722

2.3. Characteristics of Blockchain . . . . . . . . . . . . . .......................... .............................................. 6723

2.4. Types of Blockchain. . . . . ............. ........................................................................... 6724

3. Research methodology. . . . . . . . . . . . . . .................................................................................. 6724

3.1. Research questions and motives . . . . . . . . . . ............. ........................................................... 6724

3.2. Locating an apposite research engine . . . . . . ................................ ........................................ 6724

3.3. Search query string . . . . . ...................................................................... .................. 6725

https://doi.org/10.1016/j.jksuci.2022.03.007

1319-1578/Ó2022 The Authors. Published by Elsevier B.V. on behalf of King Saud University.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

⇑

Corresponding author.

E-mail addresses: ahmed.gad@fci.kfs.edu.eg (A.G. Gad), diana.mosa@yahoo.com (D.T. Mosa), Aligah.2020@gmail.com (L. Abualigah), amrabohany8@gmail.com

(A.A. Abohany).

URLs: https://ahmedgad.com (A.G. Gad), https://www.amrabohany.software (A.A. Abohany).

Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

Contents lists available at ScienceDirect

Journal of King Saud University –

Computer and Information Sciences

journal homepage: www.sciencedirect.com

3.4. Literature search protocol................................................ ........................................ 6725

4. Descriptive analysis . . . . . . . . . . . . . . . . .................................................................................. 6726

4.1. RQ1: How are Blockchain publications distributed and cited in recent years?. . . . . . . . . . . . ....................... ........... 6726

4.2. RQ2: From the number of publications, what are the main research areas investigated in Blockchain? . . . . . . . . . . .... ........... 6726

4.3. RQ3: According to the number of citations, which Blockchain papers are the most influential? . . . . . . . . . . . . . . . . ............... 6727

4.4. RQ4: Which publication venues are the most popular to publish Blockchain papers? . . . . . ....... ........................... 6727

4.5. RQ5: Which funding agencies are the topmost supportive of Blockchain research works? . . ............. ..................... 6727

4.6. RQ6: From the given main research areas, what are the key application areas of the Blockchain domain?. . . . . . . . ............... 6727

4.6.1. Financial applications. . . . . . . ............................................................................. 6729

4.6.2. Business and industrial applications . . . . . . . . . . . . . . .......................................................... 6729

4.6.3. Education ............................................................................................. 6731

4.6.4. Health-care management. . . . ............................................................................. 6731

4.6.5. Governance . . . . . . . . . . . . . . . ............................................................................. 6731

4.6.6. Security and Privacy . . . . . . . . ............................................................................. 6732

4.6.7. Internet of Things (IoT) . . . . . ............................................................................. 6732

4.6.8. Big Data management . . . . . . ............................................................................. 6733

4.6.9. Cloud and edge computing . . ............................................................................. 6733

4.6.10. Miscellaneous applications . ............................................................................. 6733

4.7. RQ7: Which are challenges and perceived deficiencies currently pressing for further investigation along with future research

opportunities? . . . . . . . . . ...................................................................... .................. 6734

4.7.1. Scalability ............................................................................................. 6734

4.7.2. Blockchain interoperability . . ............................................................................. 6734

4.7.3. Security and privacy issues . . ............................................................................. 6734

4.7.4. Quantum resilience . . . . . . . . ............................................................................. 6734

4.7.5. Selfish mining . . . . . . . . . . . . . ............................................................................. 6735

4.7.6. Artificial intelligence . . . . . . . ............................................................................. 6736

4.7.7. Lack of governance, standards, and regulations . . . . . .......................................................... 6736

5. Discussion on research streams. . . . . . . .................................................................................. 6736

6. Research validity . . . . . . . . . . . . . . . . . . .................................................................................. 6737

7. Conclusions and remarks . . . . . . . . . . . . .................................................................................. 6738

Declaration of Competing Interest . . . . .................................................................................. 6738

CRediT authorship contribution statement . . . . . . . . . . . . . . . . ............................................................... 6738

References . . . . ..................................................................................................... 6738

1. Introduction

Since the digital cryptocurrency, so-called Bitcoin, has been

innovated in 2008 (Nakamoto, 2008), a diverse range of research-

ers and practitioners have paid considerable interest to Blockchain

technology. Blockchain technology acts as the ledger used for tak-

ing records of all Bitcoin transactions as seen in Bitcoin applica-

tions (Fanning and Centers, 2016). The records of transactions are

made justly public within the Blockchain framework, putting the

aspect of privacy to the test. Everyone within the modern business

technology environment would be able to ascertain the details of

transactions because the current traditional banking system can

maintain this form of privacy through conﬁdential record-keeping.

Blockchain is roughly deﬁned as an individually connected

array of blocks, each comprising several transactions that yield a

distributed, incontrovertible data store that can be used in a broad

range of applications (Fanning and Centers, 2016), including elec-

tronic voting, crowdfunding, distributed resources, governing of

public records, and identity management. Following (Yli-Huumo

et al., 2016), currency transactions between individuals or organi-

zations are normally consolidated and managed by a third-party

company. Blockchain enables technology to act as the driving force

of the next vital revolution within the information technology per-

spective. Several implementations of Blockchain technology are

extensively used in modern-day business and each implementa-

tion has its distinct strength in various industries, ranging from

Internet of Things (IoT) (Panarello et al., 2018) and ﬁnance

(Fanning and Centers, 2016) to supply chain management

(Kshetri, 2018), health-care (Esposito et al., 2018), and reputation

systems (Dennis and Owen, 2015). Incorporating business transac-

tions, information security, privacy, and guarantee of safety within

an online environment has become necessary to enhance produc-

tion. The use of information and communication technology has

enhanced economic growth (Farhadi et al., 2012). It is worth men-

tioning that over $1 billion were invested in 2016 only by technol-

ogy companies and ﬁnancial services on deploying Blockchain.

Moreover, the next few years are expected quite to witness a dra-

matic increase in this amount (Harty, 2018).

On another side, system security concerns within the Internet

have sparked debate on the security and privacy of online transac-

tions, which the emergence of Blockchain technology development

has solved. Gupta and Dubey (2016) have explained that privacy,

security, and trust are key issues for electronic technologies in

the present day and that e-commerce security is critical to the

components that inﬂuence e-commerce, such as data security,

integrity, privacy, and other wider areas of the information secu-

rity context (Nakamoto, 2008). A primary reason why banks exist

is to intervene as a reliable and trustworthy third party in ﬁnancial

transactions (Fanning and Centers, 2016). For instance, an econ-

omy lacking banks and centers its commerce on peer-to-peer trad-

ing as a dynamic factor would make it difﬁcult for both parties in

the trade ventures to be trusted. Buying a product online does

not guarantee that the buyer would get genuine items, which could

be caused by fraud or fake product deliveries. The solution to this

stalemate is the adoption of Blockchain technology (Casino et al.,

2019), which has been proposed in this article. With the help of

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6720

Blockchain, people currently have an alternative, trusted third

party to facilitate these online transactions. Exploring Blockchain

technology subjects is critical as it fosters trust between peer-to-

peer networks due to its considerations regarding security and pri-

vacy concerns within the Internet environment for business-

oriented personalities and organizations.

Over the recent years, Blockchain technology has grown rapidly,

opening up plenty of knowledge gaps for the research community.

As a result, recent years have witnessed a remarkable amount of

research endeavors in the domain of Blockchain (Cruz et al.,

2018). Based on the data gathering method adopted in this study,

Web of Science (WoS) has been alone indexing more than 7000 sci-

entiﬁc papers in recent years. With the increasing number of pub-

lications in the Blockchain domain, comprehensive research

studies are needed to investigate an overview of the current body

of relative knowledge. To this end, researchers and practitioners

have been provided – through a few review papers – with recent

achievements and challenges regarding Blockchain (Panarello

et al., 2018). Nevertheless, it has not been yet reported a systematic

literature review of the recent scientiﬁc studies conducted under

the domain, based on WoS as a literature database. Hence, for

the steady progress in this area to be maintained, a rigorous review

of the state-of-the-art in Blockchain domain is a must to explore

the topic, adopting the major aim of providing another helpful

guide to the Blockchain community.

There appears to be a lack of concrete, systematic reviews of the

Blockchain literature in a more comprehensiveness sense. For

example, some researchers preferred to solely focus on Blockchain

applications within a certain domain (e.g., health-care Agbo et al.,

2019; Hölbl et al., 2018; Chukwu and Garg, 2020, energy sector

Andoni et al., 2019; Parmentola et al., 2021, supply chains and

logistics Pournader et al., 2020; Queiroz et al., 2019; Fosso

Wamba et al., 2020, industry Mistry et al., 2020; Li et al., 2019, edu-

cation Alammary et al., 2019, agriculture Bermeo-Almeida et al.,

2018). Others opted to discuss the QoS aspects (e.g., privacy

Liang and Ji, 2021, scalability Sanka and Cheung, 2021, security

Gupta et al., 2020) in the Blockchain. Table 1 lists some of existing

well-cited systematic literature reviews in this context and their

contrast against our study with regard to subject area (main topic),

formulation of research questions, visual representations of ﬁnd-

ings, year-wise comparisons of publication trending, and years

covered in the survey. In Table 1, it is clear the reasons why

another systematic review is necessary, highlighting how this

review is different from peers in terms of the involved aspects.

One of the most notables with the compared systematic reviews

is that each of them is closed to the discussion of a certain main

subject area and its linkage to Blockchain. For example, the studies

(Wang et al., 2019; Pournader et al., 2020; Queiroz et al., 2019) dis-

cussed only Blockchain application to supply chains. Others solely

addressed the use of Blockchain in the health-care domain (Agbo

et al., 2019; Hölbl et al., 2018), agriculture (Bermeo-Almeida

et al., 2018), business administration (Alharby and Van Moorsel,

2017; Batubara et al., 2018; Konstantinidis et al., 2018), and so

on. Also, some of these reviews are limited/very limited to either

proposing inclusive research questions, presenting reﬂective visu-

alizations, or conducting year-wise comparisons that infer trend-

ing of the underlying subject. Meanwhile, ours (present study) is

relatively more comprehensive and not tied to just one area or

domain, making it a good thorough reference for researchers and

practitioners: (i) we conduct a state-of-the-art review on Block-

chain papers indexed by WoS by formulating seven research ques-

tions along with motives behind them (see Section 3.1), (ii) a

descriptive analysis is done along with many supporting visualized

representations, pursuing satisfactory answers to the research

questions (see Section 4), and (iii) we reveal the yearly publication

trends since the inception of the Blockchain technology in 2013 up

to now.

Moreover, these above-mentioned shortcomings of previous

studies have primarily prompted us to conduct this work. In partic-

ular, this paper contributes to the systematic collection, character-

ization and analysis of the Blockchain research papers dated

between 2013 and 2020 and indexed by WoS Core Collection

(for the sake of simplicity, hereafter referred to as WoS). A system-

atic procedure was adopted to collect and select articles from the

scientiﬁc database, WoS, to realize a number of carefully picked

articles. To meet this demand, a systematic study of Blockchain lit-

erature has been undertaken to enlighten scholars and practition-

ers who are active in the Blockchain discipline. The proposed study

aims to help naive readers, researchers, and practitioners under-

stand and learn about Blockchain technology by inspiring learning

to reduce the current knowledge gap by conducting an compre-

hensive systematic review of the current WoS literature about

Table 1

Present study’s differentiation from existing systematic literature reviews.

Research Publication

year

Main topic Research

questions?

Visual

representation?

Year-wise

comparisons?

Years covered

Wang et al. (2019) 2019 Blockchain technology for future supply chains Yes No No –

Andoni et al. (2019) 2019 Blockchain technology in the energy sector No Limited No –

Alharby and Van

Moorsel (2017)

2017 Blockchain-based smart contracts Yes No No –

Agbo et al. (2019) 2019 Blockchain technology in health-care No Yes Yes 2016 – 2018

Hölbl et al. (2018) 2018 Use of Blockchain in health-care Yes Limited Yes 2015 – 2018

Pournader et al. (2020) 2020 Blockchain applications in supply chains,

transport, and logistics

Yes No No –

Queiroz et al. (2019) 2019 Blockchain and supply chain management

integration

Very limited No Yes 2013 – 2018

Batubara et al. (2018) 2018 Challenges of Blockchain technology adoption

for e-government

Very limited Very limited No 2016 – 2017

Bermeo-Almeida et al.

(2018)

2018 Blockchain in agriculture Yes Limited Very limited 2016 – 2018

Konstantinidis et al.

(2018)

2018 Blockchain for business applications Yes Very limited No 2015 – 2017

Casino et al. (2019) 2019 Blockchain-enabled applications across diverse

sectors

No Limited Yes 2014 – 2018

Taylor et al. (2020) 2020 Blockchain cyber-security applications Yes Very limited Very limited 2015 – 1018

Conoscenti et al. (2016) 2016 Blockchain for the IoT Yes No No –

Present study – A synthesis of the above Yes Yes Yes 2013 – 2021

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6721

Blockchain and its applications. This manuscript mainly synthe-

sizes the past developments in the ﬁeld along ﬁve important

dimensions:

1)Top-ten highly cited papers,

2)Annual publications and citation trends,

3)The trendiest research areas,

4)The most supportive funding agencies, and

5)The most popular publication venues for Blockchain researches.

In addition, this study sheds intense light on some key new

insights and future research directions beyond Bitcoin and cryp-

tocurrencies regarding applications of Blockchain derived from

previous studies addressed in this paper, as well as some current

open issues and challenges, opening up new avenues towards fur-

ther future researches in the ﬁeld. However, since Blockchain tech-

nology is constantly growing at a very fast pace, we have to

mention that our study cannot, in any way, be considered

exhaustive.

The remainder of the paper is organized as follows. Section 2

introduces an overview of Blockchain architecture and its working

nature. Section 3outlines the methodological approach adopted

herein to perform the systematic review. In Section 4, the retrieved

literature is analyzed descriptively. We present discussion on the

conceivable phenomena of the trends observed in the analytics

and comparisons in Section 5, threats to validity in Section 6, and

ﬁnally conclude the paper in Section 7.

2. Blockchain overview

In principle, Blockchain can be deﬁned as a digitalized public

ledger, in which all digital transactions would be recorded as a data

structure ‘‘Completed Transaction Blocks” or in chronological

order, and this is stored across a network in a distributed manner.

2.1. The structure of Blockchain

Like a public ledger, the information of all transactions is stored

in a sequence of blocks that make up the Blockchain. A reference

hash belonging to the previous block (the parent block) links these

blocks to each other. While ‘‘Genesis block” refers to the starting

block with no parent block. As shown in Fig. 1 and Table 2, a block

in Bitcoin, one major Blockchain instance, is composed of the block

header (80-byte long) which includes metadata, such as block ver-

sion (4-byte), Merkle tree root hash (32-byte), timestamp (4-byte),

nBits (4-byte), nonce (4-byte), and parent block hash (32-byte), as

well as the block body (Liang et al., 2017).

For example, in an untrustworthy environment, say the Block-

chain network, an asymmetric cryptography-based digital signa-

ture is used to validate and authenticate transactions (Zheng

et al., 2017). In this process, a private key and public key pair are

owned by each participant in the network. While the public key

used in decryption is visible to everyone and is distributed

throughout the network, the transaction is signed or encrypted

using the private key, which facilitates the decryption of the subse-

quent transaction.

2.2. How Blockchain works?

In a decentralized Blockchain network, a private key

cryptography-based digital signature is employed at a node to ini-

tiate a transaction, considered digital assets transferred as a data

structure between peers in the network. An unconﬁrmed transac-

tion pool is used to store all transactions, and a ﬂooding protocol,

known as Gossip protocol, is used to propagate those transactions

in the network. Then, based on some preset criteria, these transac-

tions need to be chosen and validated by peers (Karame et al.,

2012; Kroll et al., 2013; Nakamoto, 2008).

Consensus Agreement between various parties is roughly

deﬁned as consensus. This term originated from the idea of war,

where a few generals may prefer to attack while others prefer to

retreat. Therefore, an agreement must be reached, or mission fail-

ure is more likely to occur if only a few generals are ready for war.

Due to being a distributed network, reaching consensus in Block-

chain is a major challenge. The distributed nodes cannot be veriﬁed

for their identical ledgers by an existing central node. Therefore,

the consistency of nodes should be ensured by a protocol. Thus,

consensus plays a major role here (Zheng et al., 2017). A foolproof

consensus mechanism should maintain the coherence and sanity

of data. The problems of double-spending and Byzantine generals

could be effectively eliminated through the consensus mechanisms

of Blockchain (Gramoli, 2020). For example, Proof-of-Work (PoW),

Proof-of-Stake (PoS), and Practical Byzantine Fault Tolerance

(PBFT) are common consensus algorithms (implemented proto-

cols) by which, in certain situations, a decentralized network has

Fig. 1. Structure of a Blockchain consisting of a sequence of blocks.

Table 2

Block header components.

Component Deﬁnition

Block version Keeps track of changes and updates throughout the

protocol.

Merkle tree

root hash

Is made up of all hashed transaction hashes within the

transaction.

Timestamp Provides the date and time of day of a particular event as a

fraction of a second for a permanent, encoded record of

when that event occurred.

nBits The difﬁculty target which is simply used to adjust how

much is the hardness for the miners to manage to solve the

block.

Nonce Usually starts with 0 and increases for every hash

calculation, and is altered by miners to create different

permutations and generate a correct hash in the sequence.

Parent block

hash

Links to the previous block, or its parent block, effectively

securing the chain.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6722

to agree. A brief comparison of the Blockchain common consensus

algorithms is presented in Table 3.

To make the idea more concrete, let us assume that someone

requests a transaction of paying a number of Bitcoins to another

person, fulﬁlled by broadcasting a message in the Blockchain net-

work with information on the transaction amount and the public

address of the sender, employing digital signatures (public and pri-

vate keys) (Karame and Androulaki, 2016). To validate a transac-

tion, Blockchain uses an algorithm called Elliptical Curve Digital

Signature (ECDS), which ensures that money is only spent by its

true possessors (Yuan and Wang, 2018; Conti et al., 2018). To

sum up, the procedure for verifying and validating the requested

transaction can be outlined as follows:

1)The transaction is broadcast on a P2P (Peer to Peer) network of

nodes/computers.

2)The network of nodes uses well-known techniques, such as

ECDS, to validate the transaction and user’s status.

3)A veriﬁed transaction may be information for cryptocurrency,

records, contracts, etc.

4)Once the transaction is veriﬁed, a new block of data is created for

the ledger by linking that transaction to other transactions.

5)Then, the new block is permanently unalterably appended to the

existing Blockchain.

6)The transaction is considered valid and ﬁnal.

Fig. 2 demonstrates the veriﬁcation process, assuming a single

simple transaction (among a bunch of transactions), between two

different participants in a Blockchain network.

2.3. Characteristics of Blockchain

There are several key elements that distinguish Blockchain

technologies, which can be summarized as follows (Zheng et al.,

2017):

Decentralization: In conventional centralized systems, a central

trusted agency, say a central bank, is utilized to validate each

transaction. Therefore, trust, the main issue in decentralization,

is required – along with fail-over, availability, and lift resilience

– where a better solution could be obtained by creating a decen-

tralized P2P Blockchain architecture. Unlike a centralized

system, any two peers (P2P) can conduct a transaction in the

Blockchain network without authentication by the central

agency. That way, various consensus procedures can be used

by Blockchain to reduce the trust concern. Moreover, the server

costs (the costs of development and operation) can be reduced,

and at the central server, the performance overheads can be mit-

igated. In contrast, there are some trade-offs with Blockchain in

many cases. For example, in consensus mechanisms such as

PoW cases of Bitcoin and Ethereum, the server and energy

require higher costs, while the performance is also lower.

Persistency: Thanks to Blockchain, an infrastructure is provided

to quantify the truth (Jabbar and Bjørn, 2017) and validate the

data of producers and consumers. Assuming a 10-block Block-

chain, block No. 10 contains the previous block’s hash, and

the current block’s information is used to create a new block.

Therefore, in the existing chain, all blocks are linked together.

Current transactions are even related to the prior transaction.

Now, if any transaction is simply updated, it will signiﬁcantly

change the block’s hash. If any information is modiﬁed, the hash

data for all previous blocks must be changed, which is a difﬁcult

task that requires a great deal of work. In addition, after a miner

generates a block, other users in the network conﬁrm it. Hence,

the network will detect any potential manipulation or

falsiﬁcation of data. For this reason, Blockchain equates to an

immutable distributed ledger which can roughly be taken as

tamper-proof.

Anonymity: To avoid the exposure of identity, a user can inter-

act with a Blockchain network by having multiple randomly

generated addresses within the network (Wang et al., 2017).

As it is a decentralized system, users’ private information is

not monitored or recorded by a central authority. Given its

trustless environment, Blockchain has the potential to provide

a certain amount of anonymity.

Auditability: In a Blockchain network, a digital distributed led-

ger and a digital timestamp are used to respectively record and

validate all transactions. Therefore, if any node in the network is

accessed, previous records could be easily audited and traced

(Yu et al., 2018). For example, in Bitcoin, it is possible to itera-

tively trace all transactions, making it easy for the data state

in the Blockchain to be auditable and transparent. However,

tracing money to its origin becomes very hard when the money

is tumbled through many accounts.

Table 3

Comparison of Blockchain common consensus algorithms.

Algorithm Description Practical

example

Pros Cons

Proof-of-

Work

(PoW)

A random value ‘Nonce’ is used by miners to form the

block header for resolving a mathematical problem in the

hope of obtaining the block header’s hash value which

should not exceed the previous value or a predeﬁned

value. Thus, it is unpredictable to know who will generate

the next block in the network.

Bitcoin and

Ethereum

Very safe as it is less prone to

Sybil attacks.

51% computing power

Miners can get Bitcoins as a

reward

Prevents illegal chain fraud

High energy consumption

Driven by dedicated rewards

for solving the hash, it may

run into problems as the

rewards diminish

Proof-of-

Stake (PoS)

Blockchain adopts the randomization concept to predict

the next generator in the network. The single richest

person can dominate the network as that person is less

likely to attack the network. The underlying idea of PoS is

that it is easier to acquire computing equipment than to

acquire a digital currency.

Peercoin Potentially faster than PoW

protocol

Low energy consumption

Less potential for hardware

centralization

Reduced possibility of a selﬁsh

mining attack

Encourages miners to stick to

their stakes rather than con-

verting them into the currency

Economic penalties for fraudu-

lent attempts

Practical

Byzantine

Fault

Tolerance

(PBFT)

A new round block will be determined based on the

following rules. The entire PBFT process is divided into

three phases, which are pre-prepared, prepared, and

commit. At least two nodes’ vote is required in favor of a

node entering the next node. The node sends a request to

all other nodes in the network.

Hyperledger

Fabric

Fast and efﬁcient

Handles one-third of the faulty

or adversarial nodes

Small groups can keep a strong

organization because trust is

decoupled from resource

ownership

The exact participation of

groups must be approved by

parties

Comes at the cost of anonymity

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6723

2.4. Types of Blockchain

Typically, Blockchain technologies may fall into one of three

main categories (Zheng et al., 2017):

Public Blockchain: The transaction can be checked and veriﬁed

by everyone in the network, and the process of getting consen-

sus is also available to public. Bitcoin and Ethereum are a few

examples of a public Blockchain. Public Blockchain is shown in

Fig. 3a.

Private Blockchain: Here, the Blockchain is available for every

node to participate, the node is restricted and has strict author-

ity management to access the data. Examples of private Block-

chains include but are not limited to database management,

Bankchain, Multichain, and Monax. Private Blockchain is

depicted in Fig. 3b.

Federated/Consortium Blockchain: It is an amalgamation of

public and private Blockchains. Moreover, it means that an

authorized node can be chosen in advance. Moreover, it usually

has business-to-business partnerships. The data can also be seen

as partially decentralized. Examples of consortium Blockchain

can be Hyperledger and R3CEV. Consortium Blockchain is shown

in Fig. 3c.

Blockchain is convenient, and both have an advantage, so the

types of Blockchain do not matter. However, sometimes remote

control like private or consortium Blockchains may be needed,

depending on what place we use it or what service we offer (Lin

and Liao, 2017). Table 4 illustrates how public Blockchain, private

Blockchain, and federated/consortium Blockchain are different

from each other.

3. Research methodology

First, we present the motives behind this study and the research

questions derived from such motives. Second, we describe a num-

ber of required consecutive steps that we followed to identify rel-

evant studies. The methodology identiﬁes detailed steps to collect

the initial set of articles as well as the inclusion and exclusion cri-

teria to obtain a ﬁltered set of studies.

3.1. Research questions and motives

As mentioned earlier, this research mainly aims at conducting a

state-of-the-art review on Blockchain papers indexed by WoS. To

this end, seven Research Questions (RQs), along with motives

behind them, are outlined in Table 5. We set out to answer them.

3.2. Locating an apposite research engine

Accommodating our needs, an appropriate research engine was

pursued before collecting Blockchain papers. Among many existing

scientiﬁc databases (e.g., Scopus, EBSCO, Google Scholar, etc.), WoS

has been selected as a data source for Blockchain research. This

particular selection of WoS is attributable to several reasons: (i)

it is considered as the ﬁrst and global leading citation index in

the scientiﬁc community, (ii) it houses high-quality and inﬂuential

research publications owing to its rigorous selection process, (iii)

WoS currently covers more than 21,100 peer-reviewed, high-

quality scholarly journals (including Open Access journals), books,

and conference proceedings published worldwide, and is therefore

fully respected among academics, and (iv) it has some beneﬁcial

Fig. 2. Working nature of Blockchain.

Fig. 3. Types of Blockchain networks.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6724

analytical features which are impressive for the research

community.

3.3. Search query string

To extract the papers, we identiﬁed a query string of related

terms like ‘‘Blockchain”, ‘‘cryptocurrency”, ‘‘Bitcoin”, ‘‘Ethereum”,

and ‘‘smart contract”. The initial results of our ﬁndings are illus-

trated in Fig. 4, where the yearly publication trends are revealed

over all selected query strings. It is worth mentioning that WoS

data was accessed on 6th January 2021.

Since the publication of Nakamoto’s paper in 2008 (Nakamoto,

2008), the number of Bitcoin publications has been escalating con-

tinuously, as shown in Fig. 4. However, between 2016 and 2020,

publication trends have experienced a major change as researchers

have started paying more attention to Blockchain than other

topics. Based on our ﬁndings, in 2019 and 2020, WoS has signiﬁ-

cantly indexed 3101 and 1754 Blockchain-related research items,

respectively, thereby incentivizing us to adopt our search query

string as ‘Blockchain’. A detailed overview of our ﬁndings is given

in Table 6.

3.4. Literature search protocol

The three main parts of each paper, title, abstract, and key-

words, were minded while searching using the selected query

Table 4

Classiﬁcation and main characteristics of Blockchains.

Characteristic Public Blockchain Private Blockchain Federated/Consortium Blockchain

Access Anyone Single organization Multiple organizations

Participants Anonymous (Pseudo) Known identities Known identities

Read/Write

permission

Unpermissioned Permissioned Permissioned

Security Could be malicious Trusted Trusted

Consensus

mechanism

Consensus mechanism, PoW, PoS Pre-approvd participants (The

voting/mutliparty-consensus algorithm)

Pre-approvd participants (The

voting/mutliparty-consensus algorithm)

Network type Decentralized Partially decentralized Decentralized (a hybrid between public and

private)

Transaction

approval speed

Slow (10 min or more) Lighter and faster (100x ms) Lighter and faster (100x ms)

Data in

Blockchain

No ﬁnality Enabled ﬁnality Enabled ﬁnality

Energy

consumption

High Low Low

Scalability High High Low

Protocol efﬁciency Low High High

Transparency Low High High

Immutability Infeasible to tamper Controlled and Could be tampered Could be tampered

Observation Disruptive in terms of disintermediation Cost effective due to low latency Cost effective due to low latency

Examples Bitcoin, Ethereum, Algorand, EOS, Litecoin,

Factomm, Blockstream

Multichain, Blockstack, Bankchain Hyperledger, R3 (Banking), EWF (Energy), B3i

(Insurance), Ripple, Corda

Table 5

Research questions and motivations.

No. Question Motivation

RQ1 How are Blockchain publications

distributed and cited in recent

years?

It would help predict the future

pattern by identifying annual

publications and citation trends

in Blockchain.

RQ2 From the number of publications,

what are the main research areas

investigated in Blockchain?

It would enable researchers to

recognize the volume of research

efforts put into every area of

Blockchain, making it easier to

identify potential future research

lines.

RQ3 According to the number of

citations, which Blockchain

papers are the most inﬂuential?

It would give researchers and

practitioners a deeper insight into

the most attention-grabbing

Blockchain papers, helping them

produce high-quality research

work by adopting pioneering

studies and research methods,

thereby impressing the

Blockchain community.

RQ4 Which publication venues are the

OTHER TOPICS” (1,792 citations).

4.3. RQ3: According to the number of citations, which Blockchain

papers are the most inﬂuential?

The top 10 Blockchain papers that are most cited according to

WoS are listed in Table 7. As shown in Table 7’s most right column,

these papers are also ranked according to the yearly average cita-

tions. Up to the date of this research, a paper entitled ‘‘Blockchains

and Smart Contracts for the Internet of Things”, authored by Chris-

tidis and Devetsikiotis (Christidis and Devetsikiotis, 2016), has

been cited 941 times (within WoS) and thus ranked as the most

cited (inﬂuential) paper, among many others. The ‘‘IEEE ACCESS”

journal was the publication of this paper in 2016. In addition, the

highest annual average number of citations has been scored by this

paper. It is highly notable that of the ten highly-cited papers, the

USA has hosted ﬁve papers.

4.4. RQ4: Which publication venues are the most popular to publish

Blockchain papers?

The most popular venues with at least 80 Blockchain papers are

reported in Table 8. ‘‘IEEE ACCESS” and ‘‘LECTURE NOTES IN COM-

PUTER SCIENCE” publications have, respectively, published 50 and

43 papers, thereby proving themselves as the trendy publication

venues for Blockchain researches. To quantify their impact on the

Blockchain community, those shortlisted venues were also evalu-

ated based on other factors, including the number of citations (in

both cases with and without self-citations), per-paper average cita-

tions, and H-index. Based on the obtained results, supremacy has

been seen to relate to ‘‘IEEE ACCESS” regarding the total number

of citations and H-index, compared to other publication venues.

Notably, ‘‘FUTURE GENERATION COMPUTER SYSTEMS” ranked ﬁrst

based on the number of citations per paper, conﬁrming the jour-

nal’s reliable reference.

4.5. RQ5: Which funding agencies are the topmost supportive of

Blockchain research works?

Among the 8,435 papers analyzed in this research, the most

number of papers (i.e., 1,116 papers) have been supported by

‘‘NATIONAL NATURAL SCIENCE FOUNDATION OF CHINA” (NSFC),

followed by ‘‘NATIONAL KEY RESEARCH AND DEVELOPMENT PRO-

GRAM OF CHINA” with 317 papers, and ‘‘NATIONAL SCIENCE

FOUNDATION” (NSF) with 226 papers. Detailed information about

the most supporting funding agencies is exhibited in Fig. 10. Those

funding organizations were also evaluated in terms of the total

number of citations received by their supported papers. Accord-

ingly, Fig. 10 shows that more citations (i.e., 9,896 citations) have

been received by NSFC-backed Blockchain papers compared to

other organizations.

4.6. RQ6: From the given main research areas, what are the key

application areas of the Blockchain domain?

In this subsection, some ‘‘seminal” works (135) of the selected

papers (8,435) are solely picked based on the high impact of papers

according to the number of citations and then distributed based on

the application area. The ten main application areas based on

which the Blockchain technology has been investigated are ﬁnan-

cial applications (17 papers), business and industrial applications

(20 papers), education (9 papers), health-care management (8

papers), governance (23 papers), security and privacy (11 papers),

IoT (16 papers), Big Data management (13 papers), cloud and edge

computing (4 papers), and miscellaneous applications (14 papers).

Fig. 11 presents the percentage (%) of articles according to the

application area.

Since cryptocurrencies represent a large percentage of existing

Blockchain networks, most authors have typically categorized

Blockchain applications both into ﬁnancial and non-ﬁnancial ones

(Crosby et al., 2016; Tasatanattakool and Techapanupreeda, 2018).

Others have opted to classify them based on the Blockchain version

(i.e., 1.0, 2.0, and 3.0) (Swan, 2015; Zhao et al., 2016). In order for

this study to be more robust and comprehensive, an application-

oriented classiﬁcation is additionally proposed, similar to that pro-

posed in Casino et al. (2019) and Zhao et al. (2016). To this end,

considering the heterogeneity of Blockchain solutions, a compre-

Fig. 6. Number of Blockchain papers yearly published and indexed by WoS.

Fig. 7. Blockchain papers’ citations (within WoS) per year.

Fig. 8. Annual comparison of the total number of papers with the number of papers

not cited.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6727

Fig. 9. Coverage of knowledge domains of Blockchain papers within WoS.

Table 7

Top 10 cited Blockchain references indexed as of WoS (from 2013 to 2020).

Author(s) Paper’s title Source

(journal/confernce)

Institution (of ﬁrst

author)

Country Publication

Year

Citations

(within

WoS)

Yearly

average

citations

Christidis and

Devetsikiotis (2016)

Blockchains and Smart Contracts for

the Internet of Things

IEEE ACCESS North Carolina

State University

USA 2016 941 (#1) 235.25

(#1)

Zyskind et al. (2015) Decentralizing Privacy: Using

Blockchain to Protect Personal Data

IEEE SECURITY AND

PRIVACY WORKSHOPS

Massachusetts

Institute of

Technology

USA 2015 565 (#2) 113 (#7)

Zheng et al. (2017) An Overview of Blockchain

Technology: Architecture,

Consensus, and Future Trends

IEEE 6TH

INTERNATIONAL

CONGRESS ON BIG DATA

Sun Yat-sen

University

China 2017 444 (#3) 148 (#6)

Kosba et al. (2016) Hawk: The Blockchain Model of

Cryptography and Privacy-

Preserving Smart Contracts

IEEE SYMPOSIUM ON

SECURITY AND PRIVACY

University of

Maryland

USA 2016 431 (#4) 107.75

(#8)

Xu et al. (2018) Industry 4.0: state of the art and

future trends

INTERNATIONAL

JOURNAL OF

PRODUCTION RESEARCH

Old Dominion

University

USA 2018 429 (#5) 214.5

(#2)

Androulaki et al. (2018) Hyperledger Fabric: A Distributed

Operating System for Permissioned

Blockchains

PROCEEDINGS OF THE

THIRTEENTH EUROSYS

CONFERENCE

IBM Corporate USA 2018 403 (#6) 201.5

(#3)

Khan and Salah (2018) IoT security: Review, Blockchain

solutions, and open challenges

FUTURE GENERATION

COMPUTER SYSTEMS

Bahauddin

Zakariya

University

Pakistan 2018 396 (#7) 198 (#4)

Yli-Huumo et al. (2016) Where Is Current Research on

Blockchain Technology?-A

Systematic Review

PLOS ONE Lappeenranta-

Lahti University of

Technology

Finland 2016 382 (#8) 95.5 (#9)

Tschorsch and

Scheuermann (2016)

Bitcoin and Beyond: A Technical

Survey on Decentralized Digital

Currencies

IEEE COMMUNICATIONS

SURVEYS AND

TUTORIALS

Humboldt

University

Germany 2016 382 (#9) 95.5 (#9)

Zheng et al. (2018) Blockchain challenges and

opportunities: a survey

INTERNATIONAL

JOURNAL OF WEB AND

GRID SERVICES

Sun Yat-sen

University

China 2018 368

(#10)

184 (#5)

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6728

hensive literature review of Blockchain applications is presented,

which is visualized in Fig. 12. Below, a proper classiﬁcation is pro-

vided for the current Blockchain-enabled applications.

4.6.1. Financial applications

Currently, Blockchain technology is extensively employed in

economic transactions, prediction markets, in the settlement of

ﬁnancial assets, business services, and the ﬁnance community in

general (Haferkorn and Diaz, 2014). Blockchain is expected to have

an important representation in the sustainable development of

global economies, thus generating beneﬁts for all society, including

consumers and the current banking system.

Compared to traditional ﬁat currencies, cryptocurrencies have a

penurious reserve of value as there is no government intervention

and thus include reduced price stability. However, a speedy and

low-cost medium of exchange is provided by the Blockchain

encrypted cryptocurrencies. Several cryptocurrencies have been

developed and used for speciﬁc purposes, for example, Bitcoin, a

very successful and widely used cryptocurrency around the world

(Zheng et al., 2018). It is worth mentioning that the value of the

cryptocurrency is measured in ﬁat currency (Aras and Kulkarni,

2017). The global ﬁnancial system subsequently pursues

Blockchain-enabled applications on ﬁnancial assets (e.g., derivative

contracts, ﬁat money, securities, etc.) (Lycklama à Nijeholt et al.,

2017; Paech, 2017). For example, owing to the better performance

attained by Blockchain technology as a means of trustiness among

users, capital markets have been radically changed, and a more

efﬁcient way has been offered, to perform cryptocurrency payment

and exchange (i.e., e-wallets) (Cawrey, 2014), ﬁnancial auditing

(Dai and Vasarhelyi, 2017), general banking services (Cocco et al.,

2017), loan management schemes (Gazali et al., 2017), digital pay-

ments (Gao et al., 2018), or derivatives and securities transaction

(Wu and Liang, 2017). Notably, Barclays and Goldman Sachs, two

of the world’s biggest banks, have established a Blockchain-

enabled framework for the ﬁnancial market (Crosby et al., 2016)

by joining forces with R3

. The Global Payments Steering Group

(GPSG) (Treacher, 2016), including UniCredit, Bank of America, and

Santander, is another example of bank cooperation. XRP, created

by Ripple

, is the cryptocurrency behind GPSG, which enables global

payment and currency exchanges based on a scalable and interoper-

able open-source infrastructure.

Another interesting area that may impact cryptocurrencies

and businesses is Prediction Marketplace Systems (PMSs), which

can be considered information providers or oracles. P2P imple-

mentations of PMS based on Blockchain can be found in Team

(2017), a PoW type that permits much faster transactions than

Bitcoin, an open-source cryptocurrency featuring Scrypt Merged

mining. Under the paradigm of the wisdom of crowds, Augu

a decentralized PMS, allows users – before an event to occur –

to trade shares. Users are rewarded when future real-world events

are correctly predicted faster. Bitshares

are found in Blockchain

as digital tokens referring to speciﬁc assets like products or

currencies. Token holders may earn interest on currencies and

market products, such as gold, oil, and gas. A stack of ﬁnancial

services is offered in BitShares 2.0 in a decentralized Blockchain-

based fashion, including banking operations or currency exchange.

Coinsetter

is a platform for NYC-based Forex trading in Bitcoins.

Another example is Nasdaq-Citi (Rizzo et al., 2017), a platform

that facilitates investments in private companies, as well as rela-

tionship management.

Other ﬁnance-related areas may include over-the-counter mar-

kets, asset rehypothecation, proxy voting, automated compliance,

syndicated loans’ contingent convertible bonds, and commercial

property and casualty claims processing (McLean, 2016;

McWaters et al., 2016). Finally, Blockchain adoption will ultimately

result in cost savings in the ﬁnancial sector in areas like business

operations, centralized operations, compliance, and central ﬁnance

reporting (Treat et al., 2017).

4.6.2. Business and industrial applications

In business and management, Blockchain can be a potentially

signiﬁcant source of exciting innovation via automated, improved,

and optimized business processes (Ying et al., 2018; Houssein

et al., 2021; Houssein et al., 2021; Abualigah et al., 2022;

Abualigah et al., 2021; Abualigah et al., 2021). Many IoT-

Blockchain-based e-business models are emerging. For instance,

Zhang and Wen (2017) proposed a business model in which smart

contracts on a Blockchain distributed database are used to perform

transactions between devices. In Hardjono et al. (2016), a privacy-

preserving system was proposed based on a Blockchain-based IoT

network to – without third party authentication – prove prove-

nance manufacturing. Moreover, it has been apparent that Block-

chain applications offer commercialization opportunities and

considerable enhancement in the overall performance (Klems

et al., 2017; Kogure et al., 2017), enabling IoT companies to opti-

mize their operations and improving credibility in e-commerce

(Yoo et al., 2017) while saving cost and time. Furthermore,

Blockchain-based applications could serve several enterprises by

adopting them as business process management systems. In such

cases, the Blockchain may be used to maintain each business pro-

cess instance, and smart contracts could be employed to perform

the workﬂow routing, thereby reducing cost, as well as automating

and streamlining intra-organizational processes (Mendling et al.,

2018; Prybila et al., 2020).

Supply chain and logistics: Blockchain technology has success-

fully been integrated with the modern global supply chain.

After initially sourced goods are manufactured and distributed

to the end-user, goods are simply deﬁned as a supply chain.

Supply chain managers decisively aim to produce effective

goods for distribution to ensure customer satisfaction even if

they have to falter in the budget.

Information on product tracking, ﬂexibility, sustainability,

traceability facilities, and improved quality can be distributed

across the whole supply chain network using Blockchain tech-

nology, thus improving cost, time, and risk management. In

Zhu and Kouhizadeh (2019), the use of Blockchain for increased

accountability and transparency has been thoroughly presented

for different phases of product development. The payment can

be automated with a smart contract when returning a product

to the issuer or seller. The supply chain can have consensus-

veriﬁed real-time tracking, connecting all members on the same

platform.

In Toyoda et al. (2017), a Blockchain-based system was

designed based on consensus to diminish the counterfeits in

the supply chain through Radio Frequency Identiﬁcation (RFID)

along with the veriﬁcation of the ownership of products. In Tian

(2016), the authors proposed an RFID-based traceability system

for a Blockchain-based agri-food supply chain. In work, the trust

and traceability in the entire supply chain were proved by

transferring, processing, and distributing authentic data

(Mishra et al., 2018). Thus, the conﬂicts and judgment in the

supply chain can be deduced by the digital records created with

the Blockchain, RFID, and IoT. All critical information about

materials, product quality, location, and transaction processes

is maintained in the Blockchain-based supply chain process.

https://www.r3.com.

https://ripple.com.

https://augur.net.

https://bitshares.org.

https://www.coinsetter.com.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6729

In the current supply chain operations, there are problems in

product deletion management like logistics, reverse logistics,

manufacturing, operation, and origination, and Blockchain-

based product management has been accordingly built to

empower product deletion, and rationalization (Zhu and

Kouhizadeh, 2019).

Moreover, due to the low transparency in the current supply

chain and logistics, the reliability and traceability of the infor-

mation can be further enhanced by Blockchain-IoT combined

(Conoscenti et al., 2016), an approach to make the IoT-enabled

vehicles track the shipment process. IoT sensors about pressure,

temperature, and motion for the connected devices provide

real-time goods’ updates to be stored in the Blockchain. Once

all data is saved on the Blockchain, smart contracts get ﬁred

to allow the listed stakeholders to access the information.

Energy sector: Potential Blockchain applications in the energy

sector are broad and could immensely affect both as far as pro-

cesses and platforms (Wang and Su, 2020). For example, Block-

chain may enable new business models and marketplaces and

thus contribute to reducing costs, can engage prosumers as

enablers in the energy market in order to create energy-

efﬁcient communities, can better handle ownership, data secu-

rity, and complexity along with grids (Mengelkamp et al., 2018),

can – while preserving privacy requirements – guarantee

Table 8

Most popular publication venues for Blockchain research.

Publication venue Publications Citations Without self-citations Per-paper average citations H-index

IEEE ACCESS 516 (#1) 5,242 (#1) 4,255 10.16 33

LECTURE NOTES IN COMPUTER SCIENCE 250 (#2) 2,314 (#2) 2,167 9.26 22

SENSORS 109 (#3) 793 (#5) 713 7.28 14

IEEE INTERNET OF THINGS JOURNAL 105 (#4) 1,441 (#4) 1,311 13.72 20

IEEE 2018 INTERNATIONAL CONGRESS ON CYBERMATICS 94 (#5) 223 (#6) 223 2.37 7

FUTURE GENERATION COMPUTER SYSTEMS 81 (#6) 1,694 (#3) 1,611 20.91 19

Fig. 10. Topmost supportive funding agencies to Blockchain.

Fig. 11. Distribution of articles based on application area.

Fig. 12. Different areas of Blockchain applications.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6730

accountability, can enhance the energy market system both in

terms of transparency and trust, can support the power grid

to operate smoothly by enhancing direct P2P trading, and can

as well better manage demand response by providing an efﬁ-

cient framework toward more transactive energy operations

and effective utility billing processes (Kyriakarakos and

Papadakis, 2018). Blockchain may also be employed to issue

certiﬁcates of origin, particularly for renewable energy sources

and green energy production (Knirsch et al., 2020), to establish

energy management schemes for electric vehicles (Zhang et al.,

2018), and to develop P2P energy transaction schemes (Park

et al., 2018; Wang et al., 2019). It should be pointed out that

Blockchain technology can also act as an enabler of decarboniz-

ing the energy sector, facilitating its transition towards more

decentralized energy sources (Di Silvestre et al., 2018).

4.6.3. Education

Although Blockchain was originally devised for trustless envi-

ronments where currency transactions are carried out, it can be

applied to the online educational market if we regard the learning

process as the currency. Thus, Blockchain learning emerged

(Devine, 2015; Abdelkader et al., 2022), in which teachers could

pack and place blocks into Blockchain, thinking of the learning

achievements as coins. From this perspective, in the case of ubiqui-

tous learning environments, the issues of privacy, security, and

vulnerability can be tackled using Blockchain (Bdiwi et al., 2017),

in addition to storing educational records of reputation rewards

based on a Blockchain-based distributed system (Sharples et al.,

2016). Additionally, Blockchain can be used to improve educational

certiﬁcate management by enhancing trust and data security in

digital infrastructures (Xu et al., 2017), and for credit management

(Turkanovic

´et al., 2018). Furthermore, the digital accreditation of

academic and personal learning could be enhanced by using

Blockchain-based applications (Grech and Camilleri, 2017). School

information hubs could also be established based on Blockchain to

collect, report, and analyze data about school systems for decision-

making support (Bore et al., 2017). Finally, in scholarly publishing,

Blockchain can be adopted to better handle a manuscript submis-

sion by verifying the manuscript itself (Gipp et al., 2017) and striv-

ing to conduct appropriate reviews promptly (Spearpoint, 2017).

4.6.4. Health-care management

Recently, a digital transformation in health-care has evolved

with many health-care doctors, hospitals, and machineries to dig-

itally store the respective health records of patients. The digitized

medical data provide effortless retrieval and sharing in response to

the need to improvise decision-making based on past medical

cases, which is very beneﬁcial for maintaining records legally.

However, medical data digitization brings a high potential of viola-

tion of the patient’s privacy, and security (Xia et al., 2017; Esposito

et al., 2018). Thus, Blockchain could make a tangible impact in the

health-care industry through versatile applications in many areas,

such as public health-care management, precision medicine, clini-

cal trials, drug counterfeiting, user-oriented medical research,

sharing patients’ medical data, online patient access, automated

health claims adjudication, and longitudinal health-care records

(Al Omar et al., 2017; McGhin et al., 2019; Patel, 2019). In particu-

lar, Blockchain-enabled smart contracts could tackle issues regard-

ing ﬁndings’ scientiﬁc credibility (selective publication, data

dredging, endpoint switching, and missing data) in clinical trials

(Nugent et al., 2016), as well as problems concerning informed

consent of patients (Benchouﬁ and Ravaud, 2017).

The management of Electronic health-care Records (EHRs) of

patients is perhaps the top-ranked area with a capacity to grow

(Angraal et al., 2017; Kuo et al., 2017). When a consumer requests

for patient’s EHRs through an issuer, the Bitcoin will be placed

when the issuer (hospital or health-care) agrees with that. Before

the EHRs are sent to an information consumer, the patient, as well

as a primary doctor, must approve for only speciﬁc records to be

sent, for example, mental health records. In short, Blockchain

EHR systems can be viewed as a protocol enabling users to access

and maintain their health data, thus ensuring security and privacy

simultaneously.

4.6.5. Governance

Blockchain technology helps governments improve their ser-

vices by nurturing a more transparent government-citizen rela-

tionship. Services delivered by governments can be improved by

eliminating bureaucracy and reducing waste to prevent tax fraud.

Throughout the years, the ofﬁcial records of citizens and enter-

prises have entrusted governments with managing and holding

them. Using transaction disintermediation and record-keeping,

Blockchain-based applications might change how governments

operate at the local or state level (Hou, 2017). Blockchain’s safety,

automation, decentralization, and accountability for handling pub-

lic records could make government services more efﬁcient by

eventually obstructing corruption. In particular, in a smart city

context, business, social, and physical infrastructures could be

integrated to serve along with the adoption of Blockchain as a

secure communication platform (Jaffe et al., 2017; Bhushan et al.,

2020). The ultimate aim of Blockchain governance is to provide –

with the same validity – the same services offered by the state

and its public authorities in an efﬁcient and decentralized manner.

Such services comprise voting, taxes, marriage contracts, identiﬁ-

cation, attestation, and registration or legal documents (Swanson,

2015).

Digital identiﬁcation: Typically, two interrelated issues are

encountered with online digital identity: personally identiﬁable

information, and access control (Potts, 2019). Centralization of

information on digital identity is of societal, legal, and political

(and arguably philosophical) importance. A pioneer in the ﬁeld

is the world’s largest national digital identity scheme, released

by the Government of India, run by the Unique Identiﬁcation

Authority of India (UIDAI), with a 12-digit unique number called

Aadhaar assigned to each resident (Sen, 2019). In the digital age,

a novel and potentially revolutionary decentralization paradigm

has been imposed by Blockchain technology on digital identity.

name, access control on the Blockchain in a passcard identity

company building, is an innovative company in digital authenti-

cation. A decentralized and trustless service is provided by One-

Name so that no central institution or company can control

one’s digital identity.

Another example is the World Citizen Project (McMillan, 2014),

a decentralized passport service for across-the-globe identiﬁca-

tion of citizens. Other public services can also be provided based

on Blockchain, such as income taxation systems, patent manage-

ment, and marriage registration (Akins et al., 2014). There are

other projects focused on, such as delegate democracy, in which

the voting power is taken by delegates instead of parliamentary

representatives (Swanson, 2015). Similarly, a customizable self-

management practice, namely, Holacracy (Robertson, 2015),

was originated for organizations where self-organizing teams

– rather than setting up a typical hierarchical organization –

manage authority and decision-making.

Public sector: In public service, we consider that ofﬁcial institu-

tions do not even participate in devoting such services to

citizens as dispute resolution, reputation, virtual notary,

Proof-of-Integrity (PoI), Proof-of-Ownership (PoO), and Proof-

of-Existence (PoE). It should be noted that, in a Blockchain,

PoI, PoO, and PoE are easily veriﬁable and closely related. In

the public sector, Blockchain technology is extensively sought

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6731

by many government agencies around the world (Chiang, 2018),

particularly for utilizing inexpensive, open, distributed, and

secure database technology to increase efﬁciency by reducing

bureaucracy and cost and to authenticate many types of

persistent documents (Ølnes and Jansen, 2017). Within this

framework, other applications of Blockchain could be found:

e-residency approaches, document veriﬁcation (Sullivan and

Burger, 2017), the development of robust regulatory compliance

frameworks (De Filippi and Hassan, 2018; van Engelenburg

et al., 2019), the invention of more transparent and reliable tax-

ation mechanisms (Nemade et al., 2019), and land management

(Makala and Anand, 2018).

Voting: It has always been challenging to maintain the fairness

and privacy of current voting schemes by building a secure elec-

tronic voting system that ensures the transparency and ﬂexibil-

ity that the electronic systems provided. Therefore, shared

electronic voting systems can be implemented through the use

of Blockchain as a service for enhancing security and reducing

the monetary cost of holding nationwide elections (Boucher,

2016). A Blockchain-based electronic voting system could

ensure secure and cost-effective elections by adopting smart

contracts while ensuring voters’ privacy. A new opportunity

can certainly be offered by Blockchain technology to surmount

the barriers and constraints surrounding electronic voting sys-

tems, which lays the ground for transparency as well as ensures

the integrity and safety and of elections (Moura and Gomes,

2017). By utilizing an Ethereum private Blockchain, many trans-

actions can be sent per second using every smart contract aspect

to unburden the Blockchain. Providing higher transaction

throughput per second, speciﬁc additional measures would be

required for larger countries (Kshetri and Voas, 2018). BitCon-

gress (Hassan and De Filippi, 2021), and Liquid Democracy

(Schiener et al., 2015) are two examples of decentralized voting

systems with frameworks adopted to enforce distributed deci-

sion making. In general, Blockchain offers an independently ver-

iﬁable, decentralized, open-source, and peer-to-peer network to

be consistent with domestic legislation while gaining the conﬁ-

dence required by voters and election organizers (Hsiao et al.,

2017).

4.6.6. Security and Privacy

It can be argued that the privacy issues can be managed in

Blockchain by creating and managing digital identities through

restricting the rules and policies to accept the Blockchain model

while keeping the privacy for ownership and control (Henry

et al., 2018). With the proliferation of various mobile devices and

their services, vulnerability to malicious nodes is highly expected.

Based on pattern matching schemes, the suspected ﬁles can be

detected by proposing a number of anti-malware ﬁlters to store

and update the virus patterns on a central server. However, mali-

cious attackers can easily reach these centralized countermea-

sures. Hence, the security of distributed networks can be

signiﬁcantly improved by incorporating Blockchain technology. In

particular, in Noyes (2016), a novel anti-malware environment,

BitAV, was proposed, where users on Blockchain can distribute

the virus patterns. In this way, the fault tolerance is boosted thanks

to BitAV. It is also shown that, by using BitAV, the fault reliability

(i.e., less vulnerable to denial-of-service (DoS) attacks) can be

enhanced, and the scanning speed can be improved. Blockchain

technologies may contribute to improving the reliability of security

infrastructures. For instance, due to malicious attacks or hardware

and software ﬂaws, the dilemma of a single point of failure often

occurs with conventional Public Key Infrastructures (PKIs). Block-

chain can then be adopted for improving the reliability of conven-

tional PKIs when constructing a privacy-aware PKI (Axon, 2015).

Moreover, Liang et al. (2018) tackled modern power systems to

enhance their security against cyber-attacks based on a distributed

Blockchain protection framework. In Xu et al. (2018), Docker

con-

tainers were recalled for IoT and their beneﬁts. A novel architecture

was proposed in Rodrigues et al. (2017), which hybridizes smart con-

tract technology with Blockchain, pursuing ﬂexible and efﬁcient mit-

igation solutions for Distributed DoS (DDoS) across multiple

domains, giving a special emphasis on insecure stationery and porta-

ble devices. Tosh et al. (2017) discussed the capability to enable data

provenance in Blockchain against potential vulnerabilities. Lastly,

transactional privacy is another challenging Blockchain-related

problem. Therefore, it has been sought to improve the anonymity

of Blockchains through proposing several methods, such as zero-

knowledge proof or mixing services (Moser, 2013). Mixcoin

(Bonneau et al., 2014), and Coinjoin (Maxwell, 2013), or CoinShufﬂe

(Rufﬁng et al., 2014), are examples of implementing that technique,

which can detect dishonest transaction behaviors, and shufﬂe output

addresses by using a third party, respectively.

4.6.7. Internet of Things (IoT)

IoT is signiﬁcantly ramping up recently in the Information and

Communication Technology (ICT) domain (Abd Elaziz et al.,

2021; Abd Elaziz et al., 2021). IoT systems adopt the centralized

server-client paradigm, integrating things (or smart objects) with

cloud servers through the Internet and thus providing users with

various services (Miorandi et al., 2012; Abualigah et al., 2021).

The Blockchain and IoT technologies are already vast with their

expansion possibilities. On the other side, these two areas are myr-

iad more intertwined. For instance, despite the drawbacks encoun-

tered by distributed Wireless Sensor Networks (WSNs), which are

a pillar of technological and human evolution Kumar and Mallick

(2018), robust architectures of Blockchains may enhance their

IoT architecture by maximizing its potential while minimizing

the deﬁciencies (Kshetri, 2017; Özyilmaz and Yurdakul, 2017).

Blockchain technology and its inherent capabilities mainly drive

the investments for implementing decentralized IoT platforms

(Novo, 2018). The main idea is that in heterogeneous context-

aware scenarios, secure and auditable data are exchanged

(Casino et al., 2016) with an abundance of interconnected smart

devices (Viriyasitavat et al., 2019). Moreover, efﬁcient manage-

ment and high scalability of the network are enabled by operating

in a decentralized and automated fashion (Sharma et al., 2017).

Public and private transportation systems, and traditional com-

merce or even e-commerce can be enhanced by implementing

Blockchain-enabled, independent, and secure real-time payment

services (Christidis and Devetsikiotis, 2016). Agglomerating these

characteristics, one example of applications may be the Filecoin

(Shafagh et al., 2017), an open-source cloud storage marketplace,

protocol, and cryptocurrency. In the future, the cryptocurrency-

based bank account could be directly linked with the respective

IoT devices (Christidis and Devetsikiotis, 2016) so that services

could be handled by performing microtransactions in exchange

(Huckle et al., 2016), while in the smart grid domain, the energy

sale may also be allowed using similar approaches (Li et al.,

2017). By implementing Blockchain-based IoT solutions, several

issues could be solved, such as the high cost of maintenance in

the case of centralized approaches (Christidis and Devetsikiotis,

2016). Moreover, the security of IoT and WSNs could be increased

based on a decentralized, secure P2P model (Ouaddah et al., 2017),

keeping the systems up-to-date by providing a higher control of

IoT devices (Lee and Lee, 2017; Boudguiga et al., 2017). Undoubt-

edly, the use of Blockchain may be limited by the low capabilities

of IoT devices in terms of storage and computational power. In

https://www.docker.com.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6732

Buccafurri et al. (2017), an alternative way, a public ledger, was

proposed to overcome these drawbacks for the sake of enhancing

IoT applications. Dorri et al. (2017) presented other efﬁcient archi-

tectures; a secure, lightweight Blockchain-based model was built

tightly for adopting IoT in different application contexts.

4.6.8. Big Data management

Initially, it is a real challenge when a large amount of data needs

to be collected, stored, and operated, but the advent of data mining

and machine learning techniques have set the stage for Big Data

analysis (Hatcher and Yu, 2018). Several issues concerning privacy,

security, and centralized trust still stand in the way of the rise of

Big Data in IoT. Then, Blockchain can be adopted to manage the

decentralization of distributed data processing. Unlike other tech-

niques, Blockchain empowers data security and solves the privacy

issues in the Big Data domain (Karaﬁloski and Mishev, 2017). The

authors in (Kiyomoto et al., 2017) focused on the way to use Block-

chain technology to anonymize dataset trading. They used Hyper-

ledger Fabrica to design a Blockchain-based application, in which

the nodes – for each data transfer – collect and verify the transac-

tions. In order to stress the importance of trustiness in the Big Data

area, Yang et al. (2018) managed to ensure the safe circulation of

data resources by presenting a credible Big Data Blockchain-

based sharing model, incorporating the smart contract technology

as well. Do et al. (2017) used a keyword search service along with

cryptographic primitives to build a system enabling distributed

and secure client data management. Besides, the search and read

permissions of the data can be granted by their owner to third par-

ties. Similarly, Searchain (Jiang et al., 2020), a Blockchain-based

keyword search system, was invented to enable an efﬁcient obliv-

ious search (users are unknown to the data supplier, while they

know the chosen keyword and the corresponding ciphertext) in

decentralized storage over an authorized keyword set. For more

examples, Zyskind et al. (2015) and Azaria et al. (2016) described

systems that enable Blockchain-based decentralized distribution

of sensitive data with PoO.

Moreover, a Blockchain-based platform enables higher security

in the market of data trading and distribution. To exclusively send

secured, reliable data to centralized cloud systems, the fog com-

puters should be appropriately located in the fog computing

(Abualigah and Diabat, 2021; Houssein et al., 2021). Still, signiﬁ-

cant issues may hamper the cloud system due to drawbacks like

reprocessing and shutdown of fog computers. Major security fea-

tures are brought out by Blockchain technology thanks to digital

signature and consensus among fog computers that enable shar-

ing and controlling the authenticated transactions. Overcoming

the security issues of centralized fog computing, Jeong et al.

(2018) designed a Blockchain-based fog computing platform:

When a fog computer is a shutdown, all transactions are success-

fully restored to the fog computing by the distributed consensus

process of Blockchain. The literature has a bulk of cloud-based

efﬁcient and decentralized Blockchain solutions which can be

found in Gaetani et al. (2017) and Liang et al. (2017). Such sys-

tems enable the analysis of large volumes of transactions by com-

bating Big Data challenges (Q. Xu et al., 2018). In Jeong et al.

(2018), the security issues in fog computing have been

negotiated.

Security threats like Sybil attack, IP spooﬁng, and a single point

of failure may vulnerate centralized database systems. To ensure

security issues, Jung et al. (2017) have proposed a Blockchain-

based searching method as well as a data management system.

To check the user identity and to authenticate the information, a

digital signature was used for validation to prevent IP spooﬁng.

Such a system was developed to locate the gateway and the IP

address assigned IoT devices by combining UUIDs (Universally

Unique Identiﬁers) resulting from these devices. The transaction

includes the signature, port number, IP address, and the name.

Thus transactions can be authenticated by the signature and trace-

able through the name.

4.6.9. Cloud and edge computing

Edge computing, the processing of data at the network edge,

has shown its potential to improve response time, battery life,

bandwidth, data safety, and privacy. The services of the cloud

are pushed into the edge network. In Hatcher and Yu (2018), edge

computing has been listed for smart home, smart city, and data

sharing and collaboration between networks of long-distance.

However, it experiences several challenges concerning system

integration, resource management, the programmability of edge

computing, naming mechanisms, security and privacy issues in

transmission, storage and computation, etc. The authors (Yu

et al., 2017; Yu et al., 2013) proposed a cloud computing-based

system for enhancing cybersecurity for large enterprise networks

with reduced operational delays and can detect threats by parallel

cloud computation for both signature and anomaly-based detec-

tion. Cloud and edge computing both have a signiﬁcant applica-

tion, but with Blockchain, the distribution mechanism, and the

consensus process, cloud and edge computing challenges are

resolved. The service contract management of Blockchain for

cloud and edge computing allows programmability for the users.

Blockchain for distributed centralized large data centres brings

the consensus and decentralized layer. Sharma et al. (2017) pro-

posed a cloud architecture based on Blockchain technology with

fog computing and software-deﬁned networking for the efﬁcient

management of the data produced by the cloud and edge com-

puting. This proposed Blockchain-based architecture provides

high security, scalability, and resiliency with low latency between

the computing resources and IoT devices. The cloud computing

cost and the number of trusted third parties can be reduced sig-

niﬁcantly by this architecture. Samaniego et al. (2016) have

enlighted edge devices that are less efﬁcient in computational

resources and available bandwidth, leading to fog or cloud. By

measuring the network latency, they have used fog and cloud

to prove the potential of the IoT application with Blockchain

technology.

4.6.10. Miscellaneous applications

Blockchain-based applications outside the domains mentioned

above are to be described in this subsection. For example, cryp-

tocurrency crowd-funding platforms like Swarm, Lighthouse, and

bitFyler (Swan, 2015) are starting to use Blockchains (Buccafurri

et al., 2017; Zhu and Zhou, 2016). Blockchain can also be used to

manage event tickets securely (Tackmann et al., 2017) or to build

autonomous, distributed, secure, and intelligent transport systems

in smart city contexts (Sharma et al., 2017; Adam et al., 2020).

Blockchain applications may also be adopted as a means of ﬁghting

poverty (Kewell et al., 2017; Larios-Hernández, 2017) in the

humanitarian sector and philanthropy. As for environmental man-

agement, Blockchain technology is expected to make a powerful

impact, where it could be used within Emission Trading Schemes

as a novel ‘‘emission link” system (Fu et al., 2018). The context of

social media can be considered as another exciting application.

For instance, end-users could claim ownership, trace, and control

all their shared content based on user-centric Blockchain applica-

tions (Chakravorty and Rong, 2017). Furthermore, some exciting

IT-oriented Blockchain applications may be grid computing

(Gattermayer and Tvrdik, 2017), Blockchain as a software connec-

tor (Teslya et al., 2018), and the establishment of computational

resource sharing systems (Stanciu, 2017). Finally, Blockchain may

also contribute to improving social sharing dynamics (Pazaitis

et al., 2017).

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6733

4.7. RQ7: Which are challenges and perceived deﬁciencies currently

pressing for further investigation along with future research

opportunities?

Blockchain technology can be used in a broad spectrum of

applications to secure data with increased reliability without

requiring any central trusted authority. It has attracted researchers

due to its key characteristics: decentralization, immutability, con-

sistency, and security. However, issues and challenges arise like

any other emerging technology. In this section, certain limitations

of Blockchain are discussed, and several avenues of fruitful areas

are developed for drawing further research directions for the

future.

4.7.1. Scalability

The preﬁxed block size and block creation time are efﬁcient for

a ﬁxed number of transactions processing, but a high number of

transactions can cause slower transaction processing. Several

Blockchain applications experience the scalability issue. For exam-

ple, Bitcoin block size is 1 megabyte, and the average block conﬁr-

mation time is 10 min

. For the high transaction processing, the

block conﬁrmation time must be low, but to have the security away

from the double-spent attack in the subsequent transactions, and

this average time should be high. To solve this problem, there are

a few solutions proposed by the researchers. Kim et al. (2018) pro-

posed solutions like on- and off-chain to change for the main chain

after a transaction processing. Moreover, a side chain to change the

assets of different side chains, a child chain to record the result in the

parent chain, and an interchain for the communication between the

chains, can be potential solutions. In Henry et al. (2018), the authors

have proposed solutions like lighting protocols, sharding, etc. Fur-

thermore, Rouhani and Deters (2017) have analyzed the better per-

formance of Ethereum by addressing the scalability issues. Table 9

lists scalabilty issue-related papers along with their subject area

(main topic) and solutions proposed.

4.7.2. Blockchain interoperability

The fast pace growth in the number of Blockchain applications

created a huge number of heterogeneous solutions. However, com-

plex interoperability issues arise due to the wide diversity of fea-

tures and implementations, thereby hindering standardization. A

Bitcoin exchange-traded fund is colludely brought to the market

by many companies, especially in the U.S.

. The investment in Bit-

coins would be easier to access by users and numerous international

funds if the Bitcoin market is more regulated. However, due to the

uncontrolled growth of cryptocurrencies, different scenarios causing

a crisis may emerge, such as malicious currency exchanges or spec-

ulative attacks (Salant, 1983).

Cryptocurrencies provide many APIs, most of which are not

easy to use. Therefore, many solutions have been proposed

towards more interoperable architectures (Kosba et al., 2016).

Blockstream (Scott et al., 2017) is one of the continued efforts,

which tries to provide hardware and software solutions to compa-

nies by coordinating transactions between different Blockchains

with the major aim of creating new Blockchain-based platforms.

Furthermore, exchanging and purchasing cryptocurrencies are ser-

vices offered for gaining more adepts

. Indeed, essential security

guarantees are offered by such services for managing all types of

cryptocurrencies and purchases between cryptocurrencies and legal

course’s currencies. Table 10 lists Blockchain interoperability issue-

related papers along with their subject area (main topic) and solu-

tions proposed.

4.7.3. Security and privacy issues

There is an urgent need to research for tor offers and beyond tor

such that privacy issues can be tackled in Blockchain (Henry et al.,

2018). To create and manage digital identities, the rules and poli-

cies must be restricted to keep privacy for control and ownership

while accepting the Blockchain model. Transactional privacy is

another common problem in Blockchain data privacy. The trace-

ability of transactions and smart contract operations is of interest

to most businesses and individuals, given that they are propagated

across the network. Moreover, transactional privacy cannot be

guaranteed enough by such measures as the use of pseudonyms

(Kosba et al., 2016). For instance, transactional graph structures

of cryptocurrencies can be analyzed using existing de-

anonymization approaches (Meiklejohn et al., 2013). Moreover, it

has already been shown that much sensitive information can be

disclosed by Bitcoin’s transactions (Biryukov et al., 2014).

Given the similarities between smart contracts and programs,

errors frequently exist with smart contracts, potentially causing

hefty losses. Recent vulnerabilities include the Parity wallet

bug

, the leading cause of the theft of around $280 million, and

the Decentralized Autonomous Organization (DAO) attack (Siegel,

2016), which led to a loss of around $47 million, or thousands of

recently discovered vulnerable smart contracts (Abualigah et al.,

2021). To avoid some of the most critical smart contract vulnerabil-

ities or abuses, many proposals were written to date (Suiche, 2017).

Out of them, the most promising proposal could be approaching the

problem by limiting the underlying programming language’s expres-

siveness (Chris, 2017). Smart contract checkers (Nikolic

´et al., 2018)

is also another solution to trace the vulnerabilities of smart contracts

and to verify their fairness and correctness. Table 11 lists security

and privacy issue-related papers along with their subject area (main

topic) and solutions proposed.

4.7.4. Quantum resilience

Hashes as well as public-key encryption are two basic crypto-

graphic primitives existing at the core of Blockchain and used for

signing transactions. With the early beginnings of Blockchain,

quantum computing was way too far. However, it was a must to

radically revise the situation given recent breakthroughs

(Leymann et al., 2019).

In most Blockchains, SHA-256 is the hash algorithm, which

would be cracked using 2

128

operations using Grover’s algorithm

on a quantum computing machine. While this bolsters SHA-256

against quantum attacks, this is not the case with the public key

encryption algorithms most used in Blockchains. Once a big

enough quantum machine is built, the Elliptic Curve Digital Signa-

ture Algorithm (ECDSA) (Johnson et al., 2001), for example, will be

broken, leaving almost all Blockchains insecure. Currently, a signif-

icant effort is put into evaluating and standardizing post-quantum

cryptographic primitives. The most promising candidates for the

case of public-key cryptography originate from code-based cryp-

tography (Overbeck and Sendrier, 2009) and lattice (Micciancio

and Regev, 2009). Apparently, with Blockchain platforms currently

designed to last for years to come, a major issue at the moment is

quantum resilience. Nevertheless, in the literature, there are a few

Blockchain-based quantum-resilient approaches. For instance, in

Kiktenko et al. (2018), a quantum-safe Blockchain platform was

developed for information-theoretically secure authentication

based on an urban ﬁber network distributed quantum key. More

recently, Rajan and Visser (2019) presented a quantum networked

time machine, in which the Blockchain is encoded into a

secular Greenberger-Horne-Zeilinger state of non-simultaneously

coexisting photons. Table 12 lists quantum resilience issue-

https://blockchain.com/charts.

https://www.etf.com/channels/bitcoin.

https://www.coinbase.com.

https://www.parity.io/security-alert-2.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6734

related papers along with their subject area (main topic) and solu-

tions proposed.

4.7.5. Selﬁsh mining

Colluding selﬁsh miners have a ripe opportunity to attack a

Blockchain platform. Generally, it is convinced that the Blockchain

and the happening transaction both could be reversed by the nodes

with over 51% computing power. However, according to recent

research, the danger is still exhibited by even nodes with less

51% power. In particular, Eyal and Sirer (2014) showed that even

if cheating is being done using only a small portion of the hashing

power, the network will still be vulnerable. In selﬁsh mining strat-

egy, the mined blocks of selﬁsh miners are kept without broadcast-

ing, and the public could view the private branch only when

satisfying some requirements. All miners would admit the private

branch due to its lengthiness compared to the current public chain.

Before the publication of the private Blockchain, the resources of

honest miners are wasted on a useless branch, while the private

chain of selﬁsh miners is mined without competitors. Therefore,

more revenue should go to selﬁsh miners. The selﬁsh pool would

attract rational miners, and the selﬁsh could thus exceed 51%

power quickly.

Many other selﬁsh mining-based attacks have been proposed to

demonstrate Blockchain insecurity. In stubborn mining (Nayak

et al., 2016), miners could exploit network-level eclipse attacks

to compose mining attacks to amplify the ﬁnal gain non-trivially.

Table 9

A summary of selected papers on the scalability challenge.

Common challenge Research Subject area Findings (Potential solutions)

For the high transaction processing, the block conﬁrmation time must be low,

but to have the security away from the double-spent attack in the

subsequent transactions, and this average time should be high

Kim et al. (2018) Scalability solutions

on Blockchain

On- and off-chain to change the main

chain after a transaction processing

Aside chain to change the assets of

different side chains

A child chain to save the result in the

parent chain

An interchain for communication

between chains

Henry et al. (2018) Blockchain access

privacy

Lighting protocols

Sharding

Rouhani and Deters

(2017)

Ethereum

transactions in

private Blockchain

Pursuing better performance for

Ethereum by addressing the scalabil-

ity issues

Table 10

A summary of selected papers on the Blockchain interoperability challenge.

Common challenge Research Subject area Findings (Potential

solutions)

The fast pace growth in the number of Blockchain applications created a huge

number of heterogeneous solutions. However, complex interoperability

issues arise due to the wide diversity of features and implementations,

thereby hindering standardization

Kosba et al.

(2016)

The Blockchain model of cryptography

and privacy-preserving smart contracts

Building interoperable

architectures

Scott et al.

(2017)

Products and services form the

foundations for the ﬁnancial

infrastructure of the future

Hardware and software

solutions to companies

Coordinating transac-

tions between different

Blockchains

Table 11

A summary of selected papers on the security and privacy challenge.

Common challenge Research Subject area Findings (Potential solutions)

The traceability of transactions and smart contract operations is of

interest to most businesses and individuals, given that they are

propagated across the network. Moreover, transactional privacy

cannot be guaranteed enough by such measures as the use of

pseudonyms

Suiche

(2017)

A decompiler for Blockchain-based

smart contracts bytecode

Decompiler for ethereum virtual

machine

Bytecode into readable Solidity-

syntax contracts

Static and dynamic analysis of

compiled contracts

Chris (2017) Ethereum and solidity foundations

of Cryptocurrency and Blockchain

programming

Limiting the underlying pro-

gramming language’s

expressiveness

Nikolic

´et al.

(2018)

The greedy, prodigal, and suicidal

contracts at scale

Smart contract checkers

Tracing the vulnerabilities of

smart contracts

Verifying fairness and correct-

ness of smart contracts

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6735

One of such strategies is the ‘‘trail stubbornness”, in which the

blocks are still mined even when putting aside the private chain.

Yet, in some cases, compared to a non-trail-stubborn counterpart,

it can result in a 13% gain. Sapirshtein et al. (2016) showed that,

compared with simple selﬁsh mining, more money could be

earned, and high proﬁts can be made for smaller miners by other

selﬁsh mining strategies. However, the gains are relatively small.

Moreover, attackers can still gain from selﬁsh mining even with

less than 25% of the computational resources. In order to tackle

the underlying problem of selﬁsh mining, a novel approach was

presented by Heilman (2014) aiming at choosing which branch

to follow by honest miners. More new blocks would be selected

by honest miners, with the appeal of random beacons and times-

tamps. However, forgeable timestamps may be vulnerable to this

approach. Within ZeroBlock (Solat and Potop-Butucaru, 2016); that

is, within a maximum time interval, the network must generate

and accept each block), selﬁsh miners can hardly achieve their

expected reward. Table 13 lists selﬁsh mining issue-related papers

along with their subject area (main topic) and solutions proposed.

4.7.6. Artiﬁcial intelligence

Smart contracts could be duly utilized to tune the broad adop-

tion of Artiﬁcial Intelligence (AI) solutions, managing particular

characteristics or behaviors (e.g., autonomous drones or cars).

Moreover, a wide range of possibilities and real-time implementa-

tions may also be enabled through intelligent transactions

between entities and/or devices. New opportunities for AI applica-

tions are created by recent developments in Blockchain technology

(Omohundro, 2014). Many Blockchain challenges could be solved

with the help of AI technology. For instance, it is the responsibility

of an oracle (a generally trusted third party) to check on the satis-

faction of a contract condition. Alternatively, an intelligent oracle

may be built based on an AI technique. It just trains itself based

on learning from the outside, without control from any party. In

that way, the smart contract can become smarter with no any

argues. On the other hand, our lives are now penetrated by AI. Mis-

behavior committed by AI products could be restricted by a smart

contract integrated with Blockchain. For instance, the misbehavior

of driverless cars could be restricted by laws written in smart

contracts.

Moreover, the accuracy and effectiveness of data increase with

the race in data acquisition across many AI domains (Halevy et al.,

2009). For public Blockchain systems, interoperability and stan-

dardization will improve market prediction solutions and AI algo-

rithms since, via a public ledger, and data will be available. The

above encourage better AI models (McConaghy, 2016) and scalable,

more accurate solutions within multiple contexts, enabling data

analytics. Big data management can be much easier with the pres-

ence of a secure and veriﬁable Blockchain structure (Karaﬁloski

and Mishev, 2017). However, the use of Blockchain structure in

data analytics implies too much overhead. Though, typically, it will

not be necessary to process all transactions and, hence, it is possi-

ble to implement efﬁcient or intermediate auxiliary structures,

thereby enhancing the overall efﬁciency.

4.7.7. Lack of governance, standards, and regulations

It is indeed a major requirement to standardize the Blockchain

for its integration, interoperability, governance, sustainability, etc.

The Blockchain development must follow the rules, laws, policies,

and regulations of the government. It is challenging to manage

the governance of the Blockchain platform among different partic-

ipants. In Anjum et al. (2017), the authors have raised questions on

the Blockchain standards and standardization importance to main-

tain sustainability and trust. Moreover, the work (Kakavand et al.,

2017) has reviewed the Blockchain regulation and has measured

the performance factor. Table 14 lists lack of governance, stan-

dards, and regulations issues-related papers along with their sub-

ject area (main topic) and solutions proposed.

5. Discussion on research streams

This section discusses the trends observed by comparing and

analyzing the results in the previous section. If we closely observe

the publication trends, we can easily conclude that many research

directions have been opened up by Blockchain and have recently

received special attention from the researchers (more speciﬁcally,

since 2017). The impact of Blockchain on the research community

can be quantiﬁed by analyzing citation trends. These ﬁndings

should inform young researchers of impressive trends before

embarking on research work.

Table 12

A summary of selected papers on the quantum resilience challenge.

Common challenge Research Subject area Findings (Potential solutions)

Evaluating and standardizing post-quantum cryptographic

primitives. The most promising candidates for the case of public-

key cryptography originate from code-based cryptography and

lattice. Apparently, with current Blockchain platforms, a major

issue at the moment is quantum resilience

Kiktenko et al. (2018) Quantum-secured

Blockchain

A quantum-safe Blockchain platform for

information-theoretically secure

authentication

Releasing an urban ﬁber network dis-

tributed quantum key

Rajan and Visser (2019) Quantum

Blockchain using

entanglement in

time

A quantum networked time machine

Encoding Blockchain into a secular Green-

berger-Horne-Zeilinger state of non-simul-

taneously coexisting photons

Table 13

A summary of selected papers on the selﬁsh mining challenge.

Common challenge Research Subject area Findings (Potential solutions)

Attackers can still gain from selﬁsh

mining even with less than 25% of the

computational resources

Heilman (2014) Fresh Bitcoins Scrutinizing to ﬁnd out which branch to follow by honest miners.

More new blocks would be selected by honest miners, with the

appeal of random beacons and timestamps

Solat and Potop-

Butucaru (2016)

Timestamp-free

prevention of block-

withholding attack in

Bitcoin

ZeroBlock; that is, within a maximum time interval, the network

must generate and accept each block, with which selﬁsh miners

can hardly achieve their expected reward

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6736

Although the four underlying research areas (i.e., ‘‘COMPUTER

SCIENCE”, ‘‘ENGINEERING”, ‘‘TELECOMMUNICATIONS”, ‘‘BUSINESS

ECONOMICS”, and ‘‘SCIENCE TECHNOLOGY OTHER TOPICS”) have

been extensively covered by most of the Blockchain published

papers (see Section 4.2), exploration of the results implies that

Blockchain can be potentially applied to a wider range of research

domains. Consequently, the trendy research areas are highlighted

but opportunities for new lines of research are also uncovered.

Moreover, an abundance of helpful information is revealed by

deeply observing the highly-cited papers. This provides young

researchers with rigorous guidelines on making a paper popular,

among others, by understanding the signiﬁcant characteristics,

such as research methodology, structure, results, and evaluation.

This also helps them improve their scientiﬁc writing style. This

would also be helpful for both fresh and experienced scholars to

identify the most exciting research topics for initiating a research

project. Furthermore, a baseline for research collaboration has

been established by highlighting which authors, institutions, and

countries produce inﬂuential papers in the ﬁeld. For instance, it

was observed that American institutions are paying more attention

for conducting high-impact Blockchain researches, and therefore

more citations were received for publications by those institutions.

On the other hand, among Asian countries, China is the only active

country in producing highly-cited Blockchain publications.

Given its potential impact on the number of future citations,

selecting a suitable venue for researchers to present their research

ﬁndings is a crucial task. This demonstrates how exploring suitable

venues is important for the publication of Blockchain research.

‘‘IEEE ACCESS” and ‘‘LECTURE NOTES IN COMPUTER SCIENCE” have

been ﬂagged as the most popular venues to publish new Block-

chain contributions (see Section 4.4). However, as some subseries

and conference proceedings are covered by ‘‘LECTURE NOTES IN

COMPUTER SCIENCE”, it can be concluded that the latest Block-

chain research works are mainly published in ‘‘IEEE ACCESS”, as

the most popular venue, multidisciplinary journal. Another excit-

ing point advocating the popularity of ‘‘IEEE ACCESS” is that its

Blockchain papers have received the highest number of citations

to the date of conducting this research, followed by ‘‘LECTURE

NOTES IN COMPUTER SCIENCE” and ‘‘FUTURE GENERATION COM-

PUTER SYSTEMS”. However, the maximum ‘average citations per

paper’ rate have been largely signiﬁcantly achieved by ‘‘FUTURE

GENERATION COMPUTER SYSTEMS” in Blockchain research.

By monitoring the topmost funding organizations reported in

Section 4.5, China, among other countries, has established itself as

a major investor in Blockchain research studies. Blockchain research

papers supported by Chinese funding bodies, especially ‘‘NATIONAL

NATURAL SCIENCE FOUNDATION OF CHINA”, have been afﬁrmed to

be of high quality according to the number of their citations com-

pared to other funding agencies. Researchers and practitioners

interested in applying for a Blockchain-related position would

immensely beneﬁt from such a kind of information. Academics can

also be advised on this information before lodging a grant

application.

From the analysis (Fig. 11), it is clear that governance, business,

industrial, ﬁnancial, and IoT applications are the most focused

application areas by researchers in Blockchain technology. Indeed,

many issues have yet to be addressed while widely deploying Block-

chain applications. By doing so, Blockchain is expected to become

more scalable, efﬁcient, and durable. These offered features are not

unique if judged individually, and their bulk of mechanisms are pop-

ular for years. However, given the intense interest by several indus-

tries, all these features combined can make Blockchain ideal for

many applications. Moreover, individual characteristics required

mainly by each application domain are identiﬁed, which can facili-

tate deﬁning the Blockchain most suitable along with the corre-

sponding mechanisms to tailor the Blockchain to the application’s

actual needs. Lastly, throughout Section 4.7, some challenges and

problems hindering Blockchain development are summarized,

along with some existing approaches for solving these issues.

6. Research validity

Although our main objective in this study was to conduct a

high-quality sentiment analysis of Blockchain research studies,

some inevitable threats were imposed, which may have affected

the validity of our results. These threats, along with the actions

taken to alleviate their effects, are listed below:

Paper selection criteria: Some irrelevant or duplicate papers

could be included in the ﬁnal dataset, so the selection process

of papers was a potential threat. A methodological process

was employed to relieve the effect of this threat by excluding

papers not related to the main topic, such as letters, news items,

etc. Moreover, duplicate papers were ﬁgured out by manually

screening the initial dataset. Consequently, some repetitive

papers have been identiﬁed and excluded.

Identiﬁcation of topmost funding agencies: After extracting

the number of papers supported by each of the listed funding

agencies, we have found out that the name of the same funding

body was reported differently in some of its supported papers.

For example, some papers used the abbreviation of the funding

organization rather than its complete name. The identical names

were pursued by searching for every abbreviation separately on

the Internet to mitigate this threat. Ultimately, before reporting

the results, the number of papers with identical funding agency

names was consolidated. The only nagging threat was that

although some papers were funded, the authors did not even

acknowledge supportive agencies.

Generalizability of ﬁndings: It is a critical point to investigate

the generalizability of this study’s outcomes to external scien-

tiﬁc databases, such as Scopus, EBSCO, Google Scholar, etc.

Although this was difﬁcult to conclude, WoS has been selected

as the main literature source, driven by the fact that most of

its indexed papers have also been indexed by Scopus, EBSCO,

Google Scholar, etc. However, research fellows could replicate

this systematic study along the lines of the rigorous, transpar-

ent, and methodical approach adopted in this study, including

reports from other related databases. Conducting such replica-

tion studies could help determine the universality of this

research’s ﬁndings.

Table 14

A summary of selected papers on the lack of governance, standards, and regulations challenge.

Common challenge Research Subject area Findings (Potential solutions)

The Blockchain development must follow the rules, laws, policies,

and regulations of the government. It is challenging to manage

the governance of the Blockchain platform among different

participants

Anjum et al. (2017) Blockchain standards for

compliance and trust

Emphasizing the Blockchain standards

and standardization importance to

maintain sustainability and trust

Kakavand et al. (2017) Regulation and technology

related to distributed

ledger technologies

Reviewing the Blockchain regulation

and measuring the performance factor

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6737

Human errors: In this research, the retrieved papers were ana-

lyzed quantitatively, which may result in some human errors,

especially with complex statistical calculations performed man-

ually. Hence, this may pose the possibility of jeopardizing the

validity of our results. To avoid such a type of threat, we used

Microsoft Excel to perform all calculations automatically. Next,

the second and third authors double-checked all calculations

to ensure the reliability of the results.

7. Conclusions and remarks

In this research, a thorough explanation has been presented on

Blockchain domain based on a systematic approach. WoS was

adopted to retrieve 8,435 papers while covering the period from

2013 to 2020 through a systematic article collection and article

selection process. Prior, and for completeness, the authors have

presented the underlying architecture and mechanism of Block-

chain technology, described the key characteristics of Blockchain,

such as decentralized, immutable, distributed, and secured, and

discussed the fundamental differences between the various con-

sensus algorithms. Subsequently, from the analysis of the results

of the systematic study, it has been revealed that the recent past

four years have seen a signiﬁcant shift in research interest from

Bitcoin to Blockchain. To complement this, there has also been sig-

niﬁcant growth in the number of Blockchain papers’ citations since

2017, and most probably, the following years would continue to

witness this incremental trend.

Moreover, the paper has depicted the current research and

industrial challenges to adopt the Blockchain for different applica-

tions: scalability, interoperability, privacy and security, selﬁsh

mining, quantum resilience, and lack of governance and standard-

ization. With the wide deployment of Blockchain applications,

many issues have yet to be addressed. By doing this, the scalability

and efﬁciency of Blockchains will increase, as will their durability.

Their features are not unique to individuals, and the bulk of their

basic mechanisms have been known for years. However, combin-

ing these features makes them very suitable for different applica-

tions, thereby providing evidence for the intense interest by

several industries. As the maturity of Blockchains increases, they

become more qualiﬁed to be applied in more domains than those

covered herein. However, while Blockchains are proposed as an

alternative to databases (and panacea in some cases), this is far

from true. As already discussed, traditional databases could be

used instead in many scenarios.

Overall, a few lines of research are opened up in this study as

future work. It would be much beneﬁcial to address the highly cited

papers reported here in terms of technical aspects. Furthermore, the

same systematic study could be potentially replicated on different

literature databases, such as Scopus, EBSCO, Google Scholar, etc.,

to investigate the similarity of results with this study’s ﬁndings.

Declaration of Competing Interest

The authors declare that they have no known competing ﬁnan-

cial interests or personal relationships that could have appeared to

inﬂuence the work reported in this paper.

CRediT authorship contribution statement

Ahmed G. Gad: Conceptualization, Methodology, Validation,

Formal analysis, Investigation, Resources, Data Curation, Visualiza-

tion, Writing - original draft, Writing - review & editing. Diana T.

Mosa: Methodology, Writing - original draft, Writing - review &

editing. Laith Abualigah: Validation, Writing - review & editing.

Amr A. Abohany: Resources, Writing - review & editing.

References

M. Abd Elaziz, L. Abualigah, R.A. Ibrahim, I. Attiya, Iot workﬂow scheduling using

intelligent arithmetic optimization algorithm in fog computing, Computational

intelligence and neuroscience 2021.

M. Abd Elaziz, L. Abualigah, I. Attiya, Advanced optimization technique for

scheduling iot tasks in cloud-fog computing environments, Future Generation

Computer Systems.

H.E. Abdelkader, A.G. Gad, A.A. Abohany, S.E. Sorour, An efﬁcient data mining

technique for assessing satisfaction level of online learning for higher education

students during the covid-19, IEEE Access.

Abualigah, L.M., Diabat, A., 2021. A novel hybrid antlion optimization algorithm for

multi-objective task scheduling problems in cloud computing environments.

Clust. Comput. 24 (1), 205–223.

Abualigah, L., Diabat, A., Abd Elaziz, M., 2021. Intelligent workﬂow scheduling for

big data applications in iot cloud computing environments. Cluster Computing,

1–20.

L. Abualigah, A. Diabat, P. Sumari, A.H. Gandomi, Applications, deployments, and

integration of internet of drones (iod): A review, IEEE Sensors Journal.

Abualigah, L., Diabat, A., Mirjalili, S., Abd Elaziz, M., Gandomi, A.H., 2021. The

arithmetic optimization algorithm. Computer methods in applied mechanics

and engineering 376, 113609.

Abualigah, L., Yousri, D., Abd Elaziz, M., Ewees, A.A., Al-qaness, M.A., Gandomi, A.H.,

2021. Aquila optimizer: A novel meta-heuristic optimization algorithm.

Computers & Industrial Engineering 157, 107250.

Abualigah, L., Abd Elaziz, M., Sumari, P., Geem, Z.W., Gandomi, A.H., 2022. Reptile

search algorithm (rsa): A nature-inspired meta-heuristic optimizer. Expert Syst.

Appl. 191, 116158.

Adam, M.S., Anisi, M.H., Ali, I., 2020. Object tracking sensor networks in smart cities:

Taxonomy, architecture, applications, research challenges and future directions.

Future Generation Computer Systems 107, 909–923.

C.C. Agbo, Q.H. Mahmoud, J.M. Eklund, Blockchain technology in healthcare: a

systematic review, in: Healthcare, Vol. 7, Multidisciplinary Digital Publishing

Institute, 2019, p. 56.

Akins, B.W., Chapman, J.L., Gordon, J.M., 2014. A whole new world: Income tax

considerations of the bitcoin economy. Pitt. Tax Rev. 12, 25.

Alammary, A., Alhazmi, S., Almasri, M., Gillani, S., 2019. Blockchain-based

applications in education: A systematic review. Applied Sciences 9 (12), 2400.

M. Alharby, A. Van Moorsel, Blockchain-based smart contracts: A systematic

mapping study, arXiv preprint arXiv:1710.06372.

A. Al Omar, M.S. Rahman, A. Basu, S. Kiyomoto, Medibchain: A blockchain based

privacy preserving platform for healthcare data, in: International conference on

security, privacy and anonymity in computation, communication and storage,

Springer, 2017, pp. 534–543.

Andoni, M., Robu, V., Flynn, D., Abram, S., Geach, D., Jenkins, D., McCallum, P.,

Peacock, A., 2019. Blockchain technology in the energy sector: A systematic

review of challenges and opportunities. Renew. Sustain. Energy Rev. 100, 143–

174.

E. Androulaki, A. Barger, V. Bortnikov, C. Cachin, K. Christidis, A. De Caro, D. Enyeart,

C. Ferris, G. Laventman, Y. Manevich, et al., Hyperledger fabric: a distributed

operating system for permissioned blockchains, in: Proceedings of the

thirteenth EuroSys conference, 2018, pp. 1–15.

Angraal, S., Krumholz, H.M., Schulz, W.L., 2017. Blockchain technology: applications

in health care. Circulation: Cardiovascular quality and outcomes 10, (9)

e003800.

Anjum, A., Sporny, M., Sill, A., 2017. Blockchain standards for compliance and trust.

IEEE Cloud Computing 4 (4), 84–90.

Aras, S.T., Kulkarni, V., 2017. Blockchain and its applications–a detailed survey.

International Journal of Computer Applications 180 (3), 29–35.

Axon, L., 2015. Privacy-awareness in blockchain-based pki. Cdt technical paper

series 21, 15.

A. Azaria, A. Ekblaw, T. Vieira, A. Lippman, Medrec: Using blockchain for medical

data access and permission management, in: 2016 2nd International

Conference on Open and Big Data (OBD), IEEE, 2016, pp. 25–30.

Batubara, F.R., Ubacht, J., Janssen, M., 2018. Challenges of blockchain technology

adoption for e-government: a systematic literature review. In: Proceedings of

the 19th Annual International Conference on Digital Government Research:

Governance in the Data Age, pp. 1–9.

R. Bdiwi, C. De Runz, S. Faiz, A.A. Cherif, Towards a new ubiquitous learning

environment based on blockchain technology, in: 2017 IEEE 17th International

Conference on Advanced Learning Technologies (ICALT), IEEE, 2017, pp. 101–

102.

Benchouﬁ, M., Ravaud, P., 2017. Blockchain technology for improving clinical

research quality. Trials 18 (1), 1–5.

O. Bermeo-Almeida, M. Cardenas-Rodriguez, T. Samaniego-Cobo, E. Ferruzola-

Gómez, R. Cabezas-Cabezas, W. Bazán-Vera, Blockchain in agriculture: A

systematic literature review, in: International Conference on Technologies

and Innovation, Springer, 2018, pp. 44–56.

Bhushan, B., Khamparia, A., Sagayam, K.M., Sharma, S.K., Ahad, M.A., Debnath, N.

C., 2020. Blockchain for smart cities: A review of architectures, integration

trends and future research directions. Sustainable Cities and Society 61,

102360.

Biryukov, A., Khovratovich, D., Pustogarov, I., 2014. Deanonymisation of clients in

bitcoin p2p network. In: Proceedings of the 2014 ACM SIGSAC Conference on

Computer and Communications Security, pp. 15–29.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6738

J. Bonneau, A. Narayanan, A. Miller, J. Clark, J.A. Kroll, E.W. Felten, Mixcoin:

Anonymity for bitcoin with accountable mixes, in: International Conference on

Financial Cryptography and Data Security, Springer, 2014, pp. 486–504.

Bore, N., Karumba, S., Mutahi, J., Darnell, S.S., Wayua, C., Weldemariam, K., 2017.

Towards blockchain-enabled school information hub. In: Proceedings of the

Ninth International Conference on Information and Communication

Technologies and Development, pp. 1–4.

P. Boucher, What if blockchain technology revolutionised voting? scientiﬁc

foresight unit (stoa), european parliamentary research service, sept. 2016

(2016).

A. Boudguiga, N. Bouzerna, L. Granboulan, A. Olivereau, F. Quesnel, A. Roger, R.

Sirdey, Towards better availability and accountability for iot updates by means

of a blockchain, in: 2017 IEEE European Symposium on Security and Privacy

Workshops (EuroS&PW), IEEE, 2017, pp. 50–58.

Buccafurri, F., Lax, G., Nicolazzo, S., Nocera, A., 2017. Overcoming limits of

blockchain for IoT applications. In: Proceedings of the 12th International

Conference on Availability, Reliability and Security. Association for Computing

Machinery, pp. 1–6.

F. Buccafurri, G. Lax, S. Nicolazzo, A. Nocera, Tweetchain: An alternative to

blockchain for crowd-based applications, in: International Conference on Web

Engineering, Springer, 2017, pp. 386–393.

Casino, F., Azpilicueta, L., Lopez-Iturri, P., Aguirre, E., Falcone, F., Solanas, A., 2016.

Optimized wireless channel characterization in large complex environments by

hybrid ray launching-collaborative ﬁltering approach. IEEE Antennas Wirel.

Propag. Lett. 16, 780–783.

Casino, F., Dasaklis, T.K., Patsakis, C., 2019. A systematic literature review of

blockchain-based applications: current status, classiﬁcation and open issues.

Telematics Inform. 36, 55–81.

D. Cawrey, 37coins plans worldwide bitcoin access with sms-based wallet,

CoinDesk, May 20.

Chakravorty, A., Rong, C., 2017. Ushare: user controlled social media based on

blockchain. In: Proceedings of the 11th international conference on ubiquitous

information management and communication, pp. 1–6.

C.-W. Chiang, Blockchain for trustful collaborations between immigrants, citizens

and governments (2018).

D. Chris, Introducing ethereum and solidity foundations of cryptocurrency and

blockchain programming for beginners, Apress, New York.

Christidis, K., Devetsikiotis, M., 2016. Blockchains and smart contracts for the

internet of things, Ieee. Access 4, 2292–2303.

Chukwu, E., Garg, L., 2020. A systematic review of blockchain in healthcare:

frameworks, prototypes, and implementations. IEEE Access 8, 21196–21214.

Cocco, L., Pinna, A., Marchesi, M., 2017. Banking on blockchain: Costs savings thanks

to the blockchain technology. Future internet 9 (3), 25.

M. Conoscenti, A. Vetro, J.C. De Martin, Blockchain for the internet of things: A

systematic literature review, in: 2016 IEEE/ACS 13th International Conference

of Computer Systems and Applications (AICCSA), IEEE, 2016, pp. 1–6.

Conti, M., Kumar, E.S., Lal, C., Ruj, S., 2018. A survey on security and privacy issues of

bitcoin. IEEE Communications Surveys & Tutorials 20 (4), 3416–3452.

Crosby, M., Pattanayak, P., Verma, S., Kalyanaraman, V., et al., 2016. Blockchain

technology: Beyond bitcoin. Applied Innovation 2 (6–10), 71.

Cruz, J.P., Kaji, Y., Yanai, N., 2018. Rbac-sc: Role-based access control using smart

contract. Ieee Access 6, 12240–12251.

Dai, J., Vasarhelyi, M.A., 2017. Toward blockchain-based accounting and assurance.

Journal of Information Systems 31 (3), 5–21.

P. De Filippi, S. Hassan, Blockchain technology as a regulatory technology: From

code is law to law is code, arXiv preprint arXiv:1801.02507.

R. Dennis, G. Owen, Rep on the block: A next generation reputation system based on

the blockchain, in: 2015 10th International Conference for Internet Technology

and Secured Transactions (ICITST), IEEE, 2015, pp. 131–138.

P. Devine, Blockchain learning: can crypto-currency methods be appropriated to

enhance online learning?, in: ALT Online Winter Conference, Manchester, UK,

2015.

Di Silvestre, M.L., Favuzza, S., Sanseverino, E.R., Zizzo, G., 2018. How

decarbonization, digitalization and decentralization are changing key power

infrastructures. Renew. Sustain. Energy Rev. 93, 483–498.

H.G. Do, W.K. Ng, Blockchain-based system for secure data storage with private

keyword search, in: 2017 IEEE World Congress on Services (SERVICES), IEEE,

2017, pp. 90–93.

Dorri, A., Steger, M., Kanhere, S.S., Jurdak, R., 2017. Blockchain: A distributed

solution to automotive security and privacy. IEEE Commun. Mag. 55 (12), 119–

125.

Esposito, C., De Santis, A., Tortora, G., Chang, H., Choo, K.-K.R., 2018. Blockchain: A

panacea for healthcare cloud-based data security and privacy? IEEE Cloud

Computing 5 (1), 31–37.

I. Eyal, E.G. Sirer, Majority is not enough: Bitcoin mining is vulnerable, in:

International conference on ﬁnancial cryptography and data security,

Springer, 2014, pp. 436–454.

Fanning, K., Centers, D.P., 2016. Blockchain and its coming impact on ﬁnancial

services. J. Corporate Account. Finance 27 (5), 53–57.

Farhadi, M., Ismail, R., Fooladi, M., 2012. Information and communication

technology use and economic growth. PloS one 7, (11) e48903.

Fosso Wamba, S., Kala Kamdjoug, J.R., Epie Bawack, R., Keogh, J.G., 2020. Bitcoin,

blockchain and ﬁntech: a systematic review and case studies in the supply

chain. Production Planning & Control 31 (2–3), 115–142.

Fu, B., Shu, Z., Liu, X., 2018. Blockchain enhanced emission trading framework in

fashion apparel manufacturing industry. Sustainability 10 (4), 1105.

E. Gaetani, L. Aniello, R. Baldoni, F. Lombardi, A. Margheri, V. Sassone, Blockchain-

based database to ensure data integrity in cloud computing environments, in:

CEUR Workshop Proceedings, Vol. 1816, 2017, pp. 146–155.

Gao, F., Zhu, L., Shen, M., Sharif, K., Wan, Z., Ren, K., 2018. A blockchain-based

privacy-preserving payment mechanism for vehicle-to-grid networks. IEEE

network 32 (6), 184–192.

J. Gattermayer, P. Tvrdik, Blockchain-based multi-level scoring system for p2p

clusters, in: 2017 46th International Conference on Parallel Processing

Workshops (ICPPW), IEEE, 2017, pp. 301–308.

H.M. Gazali, R. Hassan, R.M. Nor, H.M. Rahman, Re-inventing ptptn study loan with

blockchain and smart contracts, in: 2017 8th International Conference on

Information Technology (ICIT), IEEE, 2017, pp. 751–754.

B. Gipp, C. Breitinger, N. Meuschke, J. Beel, Cryptsubmit: introducing securely

timestamped manuscript submission and peer review feedback using the

blockchain, in: 2017 ACM/IEEE Joint Conference on Digital Libraries (JCDL), IEEE,

2017, pp. 1–4.

Gramoli, V., 2020. From blockchain consensus back to byzantine consensus. Future

Generation Computer Systems 107, 760–769.

Grech, A., Camilleri, A.F., 2017. Blockchain in education. Publications Ofﬁce of the

European Union, Luxembourg.

Gupta, M.P., Dubey, A., 2016. E-commerce-study of privacy, trust and security from

consumer’s perspective. Transactions 37, 38.

Gupta, R., Tanwar, S., Kumar, N., Tyagi, S., 2020. Blockchain-based security attack

resilience schemes for autonomous vehicles in industry 4.0: A systematic

review. Computers & Electrical Engineering 86, 106717.

M. Haferkorn, J.M.Q. Diaz, Seasonality and interconnectivity within

cryptocurrencies-an analysis on the basis of bitcoin, litecoin and namecoin,

in: International Workshop on Enterprise Applications and Services in the

Finance Industry, Springer, 2014, pp. 106–120.

Halevy, A., Norvig, P., Pereira, F., 2009. The unreasonable effectiveness of data. IEEE

Intell. Syst. 24 (2), 8–12.

T. Hardjono, N. Smith, Cloud-based commissioning of constrained devices using

permissioned blockchains, in: Proceedings of the 2nd ACM international

workshop on IoT privacy, trust, and security, 2016, pp. 29–36.

D. Harty, Finance ﬁrms seen investing 1 billion in blockchain this year (2018).

Hassan, S., De Filippi, P., 2021. Decentralized autonomous organization. Internet

Policy Review 10 (2), 1–10.

Hatcher, W.G., Yu, W., 2018. A survey of deep learning: platforms, applications and

emerging research trends. IEEE Access 6, 24411–24432.

E. Heilman, One weird trick to stop selﬁsh miners: Fresh bitcoins, a solution for the

honest miner, in: International Conference on Financial Cryptography and Data

Security, Springer, 2014, pp. 161–162.

Henry, R., Herzberg, A., Kate, A., 2018. Blockchain access privacy: Challenges and

directions. IEEE Security & Privacy 16 (4), 38–45.

Hölbl, M., Kompara, M., Kamišalic

´, A., Nemec Zlatolas, L., 2018. A systematic review

of the use of blockchain in healthcare. Symmetry 10 (10), 470.

Hölbl, M., Kompara, M., Kamišalic

´, A., Nemec Zlatolas, L., 2018. A systematic review

of the use of blockchain in healthcare. Symmetry 10 (10), 470.

H. Hou, The application of blockchain technology in e-government in china, in:

2017 26th International Conference on Computer Communication and

Networks (ICCCN), IEEE, 2017, pp. 1–4.

Houssein, E.H., Gad, A.G., Wazery, Y.M., Suganthan, P.N., 2021. Task scheduling in

cloud computing based on meta-heuristics: Review, taxonomy, open

challenges, and future trends. Swarm and Evolutionary Computation 100841.

Houssein, E.H., Gad, A.G., Hussain, K., Suganthan, P.N., 2021. Major advances in

particle swarm optimization: Theory, analysis, and application. Swarm and

Evolutionary Computation 63, 100868.

Houssein, E.H., Gad, A.G., Wazery, Y.M., 2021. Jaya algorithm and applications: A

comprehensive review. Metaheuristics and Optimization in Computer and

Electrical Engineering, 3–24.

J.-H. Hsiao, R. Tso, C.-M. Chen, M.-E. Wu, Decentralized e-voting systems based on

the blockchain technology, in: Advances in Computer Science and Ubiquitous

Computing, Springer, 2017, pp. 305–309.

Huckle, S., Bhattacharya, R., White, M., Beloff, N., 2016. Internet of things,

blockchain and shared economy applications. Procedia computer science 98,

461–466.

Jabbar, K., Bjørn, P., 2017. Growing the blockchain information infrastructure. In:

Proceedings of the 2017 CHI Conference on Human Factors in Computing

Systems, pp. 6487–6498.

Jaffe, C., Mata, C., Kamvar, S., 2017. Motivating urban cycling through a blockchain-

based ﬁnancial incentives system. In: Proceedings of the 2017 ACM

International Joint Conference on Pervasive and Ubiquitous Computing and

Proceedings of the 2017 ACM International Symposium on Wearable

Computers, pp. 81–84.

Jeong, J.W., Kim, B.Y., Jang, J.W., 2018. Security and device control method for fog

computer using blockchain. In: Proceedings of the 2018 International

Conference on Information Science and System, pp. 234–238.

Jiang, P., Guo, F., Liang, K., Lai, J., Wen, Q., 2020. Searchain: Blockchain-based private

keyword search in decentralized storage. Future Generation Computer Systems

107, 781–792.

Johnson, D., Menezes, A., Vanstone, S., 2001. The elliptic curve digital signature

algorithm (ecdsa). International journal of information security 1 (1), 36–63.

M.Y. Jung, J.W. Jang, Data management and searching system and method to

provide increased security for iot platform, in: 2017 International conference on

information and communication technology convergence (ICTC), IEEE, 2017, pp.

873–878.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6739

H. Kakavand, N. Kost De Sevres, B. Chilton, The blockchain revolution: An analysis of

regulation and technology related to distributed ledger technologies, Available

at SSRN 2849251.

E. Karaﬁloski, A. Mishev, Blockchain solutions for big data challenges: A literature

review, in: IEEE EUROCON 2017-17th International Conference on Smart

Technologies, IEEE, 2017, pp. 763–768.

Karame, G.O., Androulaki, E., 2016. Bitcoin and blockchain security. Artech House.

Karame, G., Androulaki, E., Capkun, S., 2012. Two bitcoins at the price of one?

double-spending attacks on fast payments in bitcoin. IACR Cryptol. ePrint Arch.

248.

Kewell, B., Adams, R., Parry, G., 2017. Blockchain for good? Strategic Change 26 (5),

429–437.

Khan, M.A., Salah, K., 2018. Iot security: Review, blockchain solutions, and open

challenges. Future Generation Computer Systems 82, 395–411.

Kiktenko, E.O., Pozhar, N.O., Anufriev, M.N., Trushechkin, A.S., Yunusov, R.R.,

Kurochkin, Y.V., Lvovsky, A., Fedorov, A., 2018. Quantum-secured blockchain,

Quantum. Science and Technology 3, (3) 035004.

S. Kim, Y. Kwon, S. Cho, A survey of scalability solutions on blockchain, in: 2018

International Conference on Information and Communication Technology

Convergence (ICTC), IEEE, 2018, pp. 1204–1207.

S. Kiyomoto, M.S. Rahman, A. Basu, On blockchain-based anonymized dataset

distribution platform, in: 2017 IEEE 15th International Conference on Software

Engineering Research, Management and Applications (SERA), IEEE, 2017, pp.

85–92.

M. Klems, J. Eberhardt, S. Tai, S. Härtlein, S. Buchholz, A. Tidjani, Trustless

intermediation in blockchain-based decentralized service marketplaces, in:

International Conference on Service-Oriented Computing, Springer, 2017, pp.

731–739.

Knirsch, F., Brunner, C., Unterweger, A., Engel, D., 2020. Decentralized and

permission-less green energy certiﬁcates with gecko. Energy Informatics 3

(1), 1–17.

Kogure, J., Kamakura, K., Shima, T., Kubo, T., 2017. Blockchain technology for next

generation ict. Fujitsu Sci. Tech. J 53 (5), 56–61.

I. Konstantinidis, G. Siaminos, C. Timplalexis, P. Zervas, V. Peristeras, S. Decker,

Blockchain for business applications: A systematic literature review, in:

International Conference on Business Information Systems, Springer, 2018,

pp. 384–399.

A. Kosba, A. Miller, E. Shi, Z. Wen, C. Papamanthou, Hawk: The blockchain model of

cryptography and privacy-preserving smart contracts, in: 2016 IEEE symposium

on security and privacy (SP), IEEE, 2016, pp. 839–858.

J.A. Kroll, I.C. Davey, E.W. Felten, The economics of bitcoin mining, or bitcoin in the

presence of adversaries, in: Proceedings of WEIS, Vol. 2013, 2013, p. 11.

Kshetri, N., 2017. Can blockchain strengthen the internet of things? IT professional

19 (4), 68–72.

Kshetri, N., 2018. 1 blockchain’s roles in meeting key supply chain management

objectives. Int. J. Inf. Manage. 39, 80–89.

Kshetri, N., Voas, J., 2018. Blockchain-enabled e-voting. IEEE Softw. 35 (4), 95–99.

Kumar, N.M., Mallick, P.K., 2018. Blockchain technology for security issues and

challenges in iot. Procedia Computer Science 132, 1815–1823.

Kuo, T.-T., Kim, H.-E., Ohno-Machado, L., 2017. Blockchain distributed ledger

technologies for biomedical and health care applications. J. Am. Med. Inform.

Assoc. 24 (6), 1211–1220.

G. Kyriakarakos, G. Papadakis, Microgrids for productive uses of energy in the

developing world and blockchain: a promising future, Applied Sciences 8 (4).

Larios-Hernández, G.J., 2017. Blockchain entrepreneurship opportunity in the

practices of the unbanked. Bus. Horiz. 60 (6), 865–874.

Lee, B., Lee, J.-H., 2017. Blockchain-based secure ﬁrmware update for embedded

devices in an internet of things environment. The Journal of Supercomputing 73

(3), 1152–1167.

Leymann, F., Barzen, J., Falkenthal, M., 2019. Towards a platform for sharing

quantum software. In: Proceedings of the 13th Advanced Summer School on

Service Oriented Computing, pp. 70–74.

Liang, W., Ji, N., 2021. Privacy challenges of iot-based blockchain: a systematic

review. Cluster Computing, 1–19.

X. Liang, S. Shetty, D. Tosh, C. Kamhoua, K. Kwiat, L. Njilla, Provchain: A

blockchain-based data provenance architecture in cloud environment with

enhanced privacy and availability, in: 2017 17th IEEE/ACM International

Symposium on Cluster, Cloud and Grid Computing (CCGRID), IEEE, 2017, pp.

468–477.

Liang, G., Weller, S.R., Luo, F., Zhao, J., Dong, Z.Y., 2018. Distributed blockchain-based

data protection framework for modern power systems against cyber attacks.

IEEE Transactions on Smart Grid 10 (3), 3162–3173.

Li, Z., Kang, J., Yu, R., Ye, D., Deng, Q., Zhang, Y., 2017. Consortium blockchain for

secure energy trading in industrial internet of things. IEEE transactions on

industrial informatics 14 (8), 3690–3700.

Li, J., Greenwood, D., Kassem, M., 2019. Blockchain in the built environment and

construction industry: A systematic review, conceptual models and practical

use cases. Automation in Construction 102, 288–307.

Lin, I.-C., Liao, T.-C., 2017. A survey of blockchain security issues and challenges. IJ

Network Security 19 (5), 653–659.

H. Lycklama à Nijeholt, J. Oudejans, Z. Erkin, Decreg: A framework for preventing

double-ﬁnancing using blockchain technology, in: Proceedings of the ACM

Workshop on Blockchain, Cryptocurrencies and Contracts, 2017, pp. 29–34.

B. Makala, A. Anand, Blockchain and land administration (2018).

G. Maxwell, Coinjoin: Bitcoin privacy for the real world, in: Post on Bitcoin forum,

2013.

T. McConaghy, How blockchains could transform artiﬁcial intelligence,

https://dataconomy.com/2016/12/blockchains-for-artiﬁcial-intelligence (2016).

McGhin, T., Choo, K.-K.R., Liu, C.Z., He, D., 2019. Blockchain in healthcare

applications: Research challenges and opportunities. Journal of Network and

Computer Applications 135, 62–75.

J. McLean, Banking on blockchain: charting the progress of distributed ledger

technology in ﬁnancial services, A Finextra white paper produced in associate

with IBM.

R. McMillan, Hacker dreams up crypto passport using the tech behind bit-coin, San

Francisco, CA: WIRED.

R.J. McWaters, R. Galaski, S. Chatterjee, The future of ﬁnancial infrastructure: An

ambitious look at how blockchain can reshape ﬁnancial services, in: World

Economic Forum, Vol. 49, 2016, pp. 1–130.

Meiklejohn, S., Pomarole, M., Jordan, G., Levchenko, K., McCoy, D., Voelker, G.M.,

Savage, S., 2013. A ﬁstful of bitcoins: characterizing payments among men with

no names. In: in: Proceedings of the 2013 conference on Internet measurement

conference, pp. 127–140.

Mendling, J., Weber, I., Aalst, W.V.D., Brocke, J.V., Cabanillas, C., Daniel, F., Debois, S.,

Ciccio, C.D., Dumas, M., Dustdar, S., et al., 2018. Blockchains for business process

management-challenges and opportunities. ACM Transactions on Management

Information Systems (TMIS) 9 (1), 1–16.

Mengelkamp, E., Notheisen, B., Beer, C., Dauer, D., Weinhardt, C., 2018. A

blockchain-based smart grid: towards sustainable local energy markets.

Computer Science-Research and Development 33 (1), 207–214.

D. Micciancio, O. Regev, Lattice-based cryptography, in: Post-quantum

cryptography, Springer, 2009, pp. 147–191.

Miorandi, D., Sicari, S., De Pellegrini, F., Chlamtac, I., 2012. Internet of things: Vision,

applications and research challenges. Ad hoc networks 10 (7), 1497–1516.

Mishra, A.K., Kumar, A., Tripathy, A.K., Das, T.K., 2018. A two-tailed chain topology

in wireless sensor networks for efﬁcient monitoring of food grain storage. In:

Recent Findings in Intelligent Computing Techniques. Springer, pp. 97–105.

Mistry, I., Tanwar, S., Tyagi, S., Kumar, N., 2020. Blockchain for 5g-enabled iot for

industrial automation: A systematic review, solutions, and challenges.

Mechanical Systems and Signal Processing 135, 106382.

M. Moser, Anonymity of bitcoin transactions (2013).

Moura, T., Gomes, A., 2017. Blockchain voting and its effects on election

transparency and voter conﬁdence. In: Proceedings of the 18th annual

international conference on digital government research, pp. 574–575.

Nakamoto, S., 2008. Bitcoin: A peer-to-peer electronic cash system. Decentralized

Business Review, 21260.

K. Nayak, S. Kumar, A. Miller, E. Shi, Stubborn mining: Generalizing selﬁsh mining

and combining with an eclipse attack, in: 2016 IEEE European Symposium on

Security and Privacy (EuroS&P), IEEE, 2016, pp. 305–320.

A.E. Nemade, S.S. Kadam, R.N. Choudhary, S.S. Fegade, K. Agarwal, Blockchain

technology used in taxation, in: 2019 International Conference on Vision

Towards Emerging Trends in Communication and Networking (ViTECoN), IEEE,

2019, pp. 1–4.

Nikolic

´, I., Kolluri, A., Sergey, I., Saxena, P., Hobor, A., 2018. Finding the greedy,

prodigal, and suicidal contracts at scale. In: Proceedings of the 34th Annual

Computer Security Applications Conference, pp. 653–663.

Novo, O., 2018. Blockchain meets iot: An architecture for scalable access

management in iot. IEEE Internet of Things Journal 5 (2), 1184–1195.

C. Noyes, Bitav: Fast anti-malware by distributed blockchain consensus and

feedforward scanning, arXiv preprint arXiv:1601.01405.

T. Nugent, D. Upton, M. Cimpoesu, Improving data transparency in clinical trials

using blockchain smart contracts, F1000Research 5.

S. Ølnes, A. Jansen, Blockchain technology as s support infrastructure in e-

government, in: International Conference on Electronic Government, Springer,

2017, pp. 215–227.

Omohundro, S., 2014. Cryptocurrencies, smart contracts, and artiﬁcial intelligence.

AI matters 1 (2), 19–21.

A. Ouaddah, A. Abou Elkalam, A.A. Ouahman, Towards a novel privacy-preserving

access control model based on blockchain technology in iot, in: Europe and

MENA cooperation advances in information and communication technologies,

Springer, 2017, pp. 523–533.

R. Overbeck, N. Sendrier, Code-based cryptography, in: Post-quantum cryptography,

Springer, 2009, pp. 95–145.

Özyilmaz, K., Yurdakul, A., 2017. Work-in-progress: integrating low-power iot

devices to a blockchain-based infrastructure. In: Proceedings of the 13th ACM

International Conference on Embedded Software, pp. 1–2.

Paech, P., 2017. The governance of blockchain ﬁnancial networks. The Modern Law

Review 80 (6), 1073–1110.

Panarello, A., Tapas, N., Merlino, G., Longo, F., Puliaﬁto, A., 2018. Blockchain and iot

integration: A systematic survey. Sensors 18 (8), 2575.

Park, L.W., Lee, S., Chang, H., 2018. A sustainable home energy prosumer-chain

methodology with energy tags over the blockchain. Sustainability 10 (3), 658.

A. Parmentola, A. Petrillo, I. Tutore, F. De Felice, Is blockchain able to enhance

environmental sustainability? a systematic review and research agenda from

the perspective of sustainable development goals (sdgs), Business Strategy and

the Environment.

Patel, V., 2019. A framework for secure and decentralized sharing of medical

imaging data via blockchain consensus. Health informatics journal 25 (4),

1398–1411.

Pazaitis, A., De Filippi, P., Kostakis, V., 2017. Blockchain and value systems in the

sharing economy: The illustrative case of backfeed. Technol. Forecast. Soc.

Chang. 125, 105–115.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6740

J. Potts, Blockchain and government, Data61?Future of Blockchain?Report, June.

Pournader, M., Shi, Y., Seuring, S., Koh, S.L., 2020. Blockchain applications in supply

chains, transport and logistics: a systematic review of the literature. Int. J. Prod.

Res. 58 (7), 2063–2081.

Prybila, C., Schulte, S., Hochreiner, C., Weber, I., 2020. Runtime veriﬁcation for

business processes utilizing the bitcoin blockchain. Future Generation

Computer Systems 107, 816–831.

M.M. Queiroz, R. Telles, S.H. Bonilla, Blockchain and supply chain management

integration: a systematic review of the literature, Supply Chain Management:

An International Journal.

Q. Xu, K.M.M. Aung, Y. Zhu, K.L. Yong, A blockchain-based storage system for data

analytics in the internet of things, in: New Advances in the Internet of Things,

Springer, 2018, pp. 119–138.

Rajan, D., Visser, M., 2019. Quantum blockchain using entanglement in time.

Quantum Reports 1 (1), 3–11.

P. Rizzo, Nasdaq and citi announce pioneering blockchain and global banking

integration (2017).

B.J. Robertson, Holacracy: The revolutionary management system that abolishes

hierarchy, Penguin UK, 2015.

Rodrigues, B., Bocek, T., Lareida, A., Hausheer, D., Rafati, S., Stiller, B., 2017. A

blockchain-based architecture for collaborative ddos mitigation with smart

contracts. In: IFIP International Conference on Autonomous Infrastructure,

Management and Security. Springer, Cham, pp. 16–29.

S. Rouhani, R. Deters, Performance analysis of ethereum transactions in private

blockchain, in: 2017 8th IEEE International Conference on Software Engineering

and Service Science (ICSESS), IEEE, 2017, pp. 70–74.

T. Rufﬁng, P. Moreno-Sanchez, A. Kate, Coinshufﬂe: Practical decentralized coin

mixing for bitcoin, in: European Symposium on Research in Computer Security,

Springer, 2014, pp. 345–364.

Salant, S.W., 1983. The vulnerability of price stabilization schemes to speculative

attack. Journal of Political Economy 91 (1), 1–38.

M. Samaniego, U. Jamsrandorj, R. Deters, Blockchain as a service for iot, in: 2016

IEEE international conference on internet of things (iThings) and IEEE green

computing and communications (GreenCom) and IEEE cyber, physical and

social computing (CPSCom) and IEEE smart data (SmartData), IEEE, 2016, pp.

433–436.

Sanka, A.I., Cheung, R.C., 2021. A systematic review of blockchain scalability: Issues,

solutions, analysis and future research. Journal of Network and Computer

Applications 195, 103232.

A. Sapirshtein, Y. Sompolinsky, A. Zohar, Optimal selﬁsh mining strategies in

bitcoin, in: International Conference on Financial Cryptography and Data

Security, Springer, 2016, pp. 515–532.

D. Schiener, Liquid democracy: True democracy for the 21st century, Medium:

Organizer Sandbox (November 23, 2015), https://medium. com/

organizersandbox/liquid-democracy-true-democracy-for-the-21st-century-

7c66f5e53b6f.

Scott, B., Loonam, J., Kumar, V., 2017. Exploring the rise of blockchain technology:

Towards distributed collaborative organizations. Strategic Change 26 (5), 423–

428.

S. Sen, A decade of aadhaar: Lessons in implementing a foundational id system, ORF

Issue Brief No 292.

Shafagh, H., Burkhalter, L., Hithnawi, A., Duquennoy, S., 2017. Towards blockchain-

based auditable storage and sharing of iot data. In: Proceedings of the 2017 on

cloud computing security workshop, pp. 45–50.

Sharma, P.K., Chen, M.-Y., Park, J.H., 2017. A software deﬁned fog node based

distributed blockchain cloud architecture for iot. Ieee Access 6, 115–124.

M. Sharples, J. Domingue, The blockchain and kudos: A distributed system for

educational record, reputation and reward, in: European conference on

technology enhanced learning, Springer, 2016, pp. 490–496.

D. Siegel, Understanding the dao attack, Retrieved June 13 (2016) 2018.

S. Solat, M. Potop-Butucaru, Zeroblock: Timestamp-free prevention of block-

withholding attack in bitcoin, arXiv preprint arXiv:1605.02435.

Spearpoint, M., 2017. A proposed currency system for academic peer review

payments using the blockchain technology. Publications 5 (3), 19.

A. Stanciu, Blockchain based distributed control system for edge computing, in:

2017 21st International Conference on Control Systems and Computer Science

(CSCS), IEEE, 2017, pp. 667–671.

M. Suiche, Porosity: A decompiler for blockchain-based smart contracts bytecode,

DEF con 25 (11).

Sullivan, C., Burger, E., 2017. E-residency and blockchain. Computer law & security

review 33 (4), 470–481.

Swan, M., 2015. Blockchain: Blueprint for a new economy. O’Reilly Media Inc.

T. Swanson, Consensus-as-a-service: a brief report on the emergence of

permissioned, distributed ledger systems, Report, available online.

B. Tackmann, Secure event tickets on a blockchain, in: Data privacy management,

Cryptocurrencies and Blockchain technology, Springer, 2017, pp. 437–444.

P. Tasatanattakool, C. Techapanupreeda, Blockchain: Challenges and applications,

in: 2018 International Conference on Information Networking (ICOIN), IEEE,

2018, pp. 473–475.

Taylor, P.J., Dargahi, T., Dehghantanha, A., Parizi, R.M., Choo, K.-K.R., 2020. A

systematic literature review of blockchain cyber security. Digital

Communications and Networks 6 (2), 147–156.

V.D. Team, Viacoin whitepaper (2017).

N. Teslya, A. Smirnov, Blockchain-based framework for ontology-oriented robots?

coalition formation in cyberphysical systems, in: MATEC Web of Conferences,

Vol. 161, EDP Sciences, 2018, p. 03018.

F. Tian, An agri-food supply chain traceability system for china based on rﬁd &

blockchain technology, in: 2016 13th international conference on service

systems and service management (ICSSSM), IEEE, 2016, pp. 1–6.

D.K. Tosh, S. Shetty, X. Liang, C.A. Kamhoua, K.A. Kwiat, L. Njilla, Security

implications of blockchain cloud with analysis of block withholding attack,

in: 2017 17th IEEE/ACM International Symposium on Cluster, Cloud and Grid

Computing (CCGRID), IEEE, 2017, pp. 458–467.

Toyoda, K., Mathiopoulos, P.T., Sasase, I., Ohtsuki, T., 2017. A novel blockchain-based

product ownership management system (poms) for anti-counterfeits in the

post supply chain. IEEE access 5, 17465–17477.

M. Treacher, Announcing ripple’s global payments steering group?, Ripple. Insights

23.

Treat, D., Brodersen, C., Blain, C., Kurbanov, R., 2017. Banking on blockchain-a value

analysis for investment banks. Accent. Consult, 10.

Tschorsch, F., Scheuermann, B., 2016. Bitcoin and beyond: A technical survey on

decentralized digital currencies. IEEE Communications Surveys & Tutorials 18

(3), 2084–2123.

Turkanovic

´, M., Hölbl, M., Košic

ˇ, K., Heric

ˇko, M., Kamišalic

´, A., 2018. Eductx: A

blockchain-based higher education credit platform. IEEE access 6, 5112–5127.

van Engelenburg, S., Janssen, M., Klievink, B., 2019. Design of a software

architecture supporting business-to-government information sharing to

improve public safety and security. Journal of Intelligent information

systems 52 (3), 595–618.

Viriyasitavat, W., Anuphaptrirong, T., Hoonsopon, D., 2019. When blockchain meets

internet of things: Characteristics, challenges, and business opportunities.

Journal of industrial information integration 15, 21–28.

Wang, Q., Su, M., 2020. Integrating blockchain technology into the energy sector

from theory of blockchain to research and application of energy blockchain.

Computer Science Review 37, 100275.

Wang, Q., Li, X., Yu, Y., 2017. Anonymity for bitcoin from secure escrow address.

IEEE Access 6, 12336–12341.

Y. Wang, J.H. Han, P. Beynon-Davies, Understanding blockchain technology for

future supply chains: a systematic literature review and research agenda,

Supply Chain Management: An International Journal.

Wang, S., Taha, A.F., Wang, J., Kvaternik, K., Hahn, A., 2019. Energy crowdsourcing

and peer-to-peer energy trading in blockchain-enabled smart grids. IEEE

Transactions on Systems, Man, and Cybernetics: Systems 49 (8), 1612–1623.

T. Wu, X. Liang, Exploration and practice of inter-bank application based on

blockchain, in: 2017 12th International Conference on Computer Science and

Education (ICCSE), IEEE, 2017, pp. 219–224.

Xia, Q., Sifah, E.B., Smahi, A., Amofa, S., Zhang, X., 2017. Bbds: Blockchain-based data

sharing for electronic medical records in cloud environments. Information 8 (2),

44.

Y. Xu, S. Zhao, L. Kong, Y. Zheng, S. Zhang, Q. Li, Ecbc: A high performance

educational certiﬁcate blockchain with efﬁcient query, in: International

Colloquium on Theoretical Aspects of Computing, Springer, 2017, pp. 288–

304.

Xu, Q., Jin, C., Rasid, M.F.B.M., Veeravalli, B., Aung, K.M.M., 2018. Blockchain-based

decentralized content trust for docker images. Multimedia Tools and

Applications 77 (14), 18223–18248.

Xu, L.D., Xu, E.L., Li, L., 2018. Industry 4.0: state of the art and future trends. Int. J.

Prod. Res. 56 (8), 2941–2962.

Yang, C., Chen, X., Xiang, Y., 2018. Blockchain-based publicly veriﬁable data deletion

scheme for cloud storage. Journal of Network and Computer Applications 103,

185–193.

Ying, W., Jia, S., Du, W., 2018. Digital enablement of blockchain: Evidence from hna

group. Int. J. Inf. Manage. 39, 1–4.

Yli-Huumo, J., Ko, D., Choi, S., Park, S., Smolander, K., 2016. Where is current

research on blockchain technology?–a systematic review. PloS one 11, (10)

e0163477.

M. Yoo, Y. Won, Study on smart automated sales system with blockchain-based

data storage and management, in: Advances in Computer Science and

Ubiquitous Computing, Springer, 2017, pp. 734–740.

Yuan, Y., Wang, F.-Y., 2018. Blockchain and cryptocurrencies: Model, techniques,

and applications. IEEE Transactions on Systems, Man, and Cybernetics: Systems

48 (9), 1421–1428.

W. Yu, G. Xu, Z. Chen, P. Moulema, A cloud computing based architecture for cyber

security situation awareness, in: 2013 iEEE conference on communications and

network security (cNS), IEEE, 2013, pp. 488–492.

Yu, W., Liang, F., He, X., Hatcher, W.G., Lu, C., Lin, J., Yang, X., 2017. A survey on the

edge computing for the internet of things. IEEE access 6, 6900–6919.

Yu, H., Yang, Z., Sinnott, R.O., 2018. Decentralized big data auditing for smart city

environments leveraging blockchain technology. IEEE Access 7, 6288–6296.

Zhang, Y., Wen, J., 2017. The iot electric business model: Using blockchain

technology for the internet of things. Peer-to-Peer Networking and

Applications 10 (4), 983–994.

Zhang, T., Pota, H., Chu, C.-C., Gadh, R., 2018. Real-time renewable energy incentive

system for electric vehicles using prioritization and cryptocurrency. Applied

energy 226, 582–594.

J.L. Zhao, S. Fan, J. Yan, Overview of business innovations and research opportunities

in blockchain and introduction to the special issue (2016).

Z. Zheng, S. Xie, H. Dai, X. Chen, H. Wang, An overview of blockchain technology:

Architecture, consensus, and future trends, in: 2017 IEEE international congress

on big data (BigData congress), IEEE, 2017, pp. 557–564.

Zheng, Z., Xie, S., Dai, H.-N., Chen, X., Wang, H., 2018. Blockchain challenges and

opportunities: A survey. Int. J. Web Grid Serv. 14 (4), 352–375.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

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Zhu, Q., Kouhizadeh, M., 2019. Blockchain technology, supply chain information,

and strategic product deletion management. IEEE Eng. Manage. Rev. 47 (1), 36–

44.

Zhu, H., Zhou, Z.Z., 2016. Analysis and outlook of applications of blockchain

technology to equity crowdfunding in china. Financial innovation 2 (1), 1–11.

G. Zyskind, O. Nathan, et al., Decentralizing privacy: Using blockchain to protect

personal data, in: 2015 IEEE Security and Privacy Workshops, IEEE, 2015, pp.

180–184.

Ahmed G. Gad received the B.Sc. (Hons.) degree from

the Faculty of Computers and Information, Mansoura

University, Mansoura, Egypt, in 2013. Since 2017, he has

been a full-time Teaching Assistant of Information

Technology with the Faculty of Computers and Infor-

mation, Kafrelsheikh University, Kafrelsheikh, Egypt.

His current major research interests span Meta-

heuristics, Optimization, Machine Learning, Data min-

ing, Cloud Computing, Scheduling, and Blockchain.

Diana T. Mosa received the Ph.D. degree from Mansoura

University, Egypt, in 2014. She has more than 5 scien-

tiﬁc research papers published in prestigious interna-

tional journals in the topics of information systems. Her

current research interests include the Internet of Things,

Machine Learning, and Optimization.

Laith Abualigah received his ﬁrst degree from Al-Albayt

University, Computer Information System, Jordan, in

2011. He earned the M.Sc. degree from Al-Albayt

University, Computer Science, Jordan, in 2014. He

received the Ph.D. degree from the School of Computer

Science in Universiti Sains Malaysia (USM), Malaysia, in

2018. He is an Assistant Professor with the Computer

Science Department, Amman Arab University, Jordan.

He is also a distinguished researcher at the School of

Computer Science, Universiti Sains Malaysia, Malaysia.

According to the report published by Stanford Univer-

sity in 2020, Abualigah is one of the 2% inﬂuential

scholars, which depicts the 100,000 top scientists in the world. Abualigah has

published more than 130 journal papers and books, which collectively have been

cited more than 4700 times (H-index = 32). His main research interests focus on

Arithmetic Optimization Algorithm (AOA), Bio-inspired Computing, Nature-

inspired Computing, Swarm Intelligence, Artiﬁcial Intelligence, Meta-heuristic

Modeling, and Optimization Algorithms, Evolutionary Computations, Information

Retrieval, Text clustering, Feature Selection, Combinatorial Problems, Optimization,

Advanced Machine Learning, Big data, and Natural Language Processing. Abualigah

currently serves as an associate editor of the journals, Cluster Computing (Springer),

Soft Computing (Springer), and Journal of King Saud University - Computer and

Information Sciences (Elsevier).

Amr A. Abohany received the B.Sc. degree from the

Faculty of Computers and Information, Zagazig Univer-

sity, Egypt, in 2007, and the M.Sc. and Ph.D. degrees

from the Faculty of Computers and Information, Helwan

University, Egypt, in 2014 and 2018, respectively. He

has more than 11 scientiﬁc research articles published

in prestigious international journals in the topics of

information systems. His current research interests

include Optimization, Machine Learning, and the Inter-

net of Things.

A.G. Gad, D.T. Mosa, L. Abualigah et al. Journal of King Saud University – Computer and Information Sciences 34 (2022) 6719–6742

6742

A systematic review of Blockchain application in Smart cities: Trends and Opportunities

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Jan 2025

The growth of the urban population has fueled the development of smarter cities. 13 Smart cities built on blockchain have proven to have increased resilience to security threats, 14 increased reliability, and many other advantages. This paper examines how blockchain has been 15 implemented in the smart city infrastructure to date. Looking at existing research between 2013 16 and 2022, we investigate how blockchain research has evolved in a decade especially, the trig-17 gers for the boom in research in 2017, and how the trends have changed to date. Although by 18 2018, researchers were trying different concepts and exploring the potential in different fields, 19 the COVID-19 pandemic was the only strong external factor that caused a shift in the trend to-20 ward smart health. However, despite the pandemic, the smart health research spike was very 21 brief as there was more research on smart economy and smart living. Therefore, as blockchain 22 expands there are a lot of challenges that need to be resolved. Thus, this paper also discusses 23 the challenges associated with blockchain-based smart cities and possible solutions using AI 24 convergence. 25

LEVERAGING BLOCKCHAIN TECHNOLOGY FOR ENHANCED BUSINESS INTELLIGENCE DATA MANAGEMENT

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This article explores the transformative impact of blockchain technology integration within Business Intelligence (BI) systems, addressing critical challenges in data integrity, trust, and governance. The article examines how blockchain's distributed ledger technology enhances data management practices across various industries, particularly focusing on security, transparency, and operational efficiency. Through a comprehensive article of enterprise implementations, the article demonstrates significant improvements in data verification, compliance monitoring, and cross-departmental collaboration. The article covers key aspects including automated verification mechanisms, decentralized governance models, and smart contract implementation, while also addressing scalability challenges and integration complexities. The findings reveal how blockchain technology fundamentally revolutionizes traditional BI infrastructure, offering robust solutions for data quality assurance and regulatory compliance while enabling sustainable and efficient data management practices.

Adoption of Blockchain Technology to Secure Electronic Health Record Systems

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Dec 2024

This quantitative, non-experimental study examined the potential of blockchain technology to enhance the security of Electronic Health Record (EHR) systems through decentralization. Using the Technology Acceptance Model (TAM) framework, the research explored the correlation between perceived usefulness (PU), perceived ease of use (PEOU), regulatory compliance (RC), security concerns (SC), trust (TR), and behavioral intention (BI) to adopt blockchain for EHR security. A survey was conducted among professionals with expertise in blockchain, information security, and cybersecurity. Spearman’s rank correlation analysis found statistically significant relationships between these factors and blockchain adoption for EHR security. The study suggests further research into blockchain applications in radiology to improve performance.

Integrating Blockchain Technology for Privacy-Preserving and Tamper-Proof Electronic Voting in Modern Electoral Systems

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Future Directions in Digital Forensics and Cybersecurity

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Mar 2025

Digital forensics and cybersecurity fields constantly change to keep up with emerging technologies and evolving threats. This chapter offers valuable insight into the prospects of these fields, with a focus on key trends and challenges. It explores the potential impact of groundbreaking technologies like quantum computing , Blockchain, and artificial intelligence on digital forensics and cybersecu-rity. Moreover, it highlights the growing importance of automation and machine learning in digital forensics while examining the changing nature of cyber threats. The chapter emphasizes the need for collaborative, interdisciplinary approaches to combat future threats effectively. It also stresses the ethical and human elements that require careful consideration in developing and implementing upcoming digital forensics and cybersecurity practices. As these fields evolve, professionals and researchers must stay abreast of these trends and challenges.

Optimizing Blockchain Network Performance Using Blake3 Hash Function in POS Consensus Algorithm

Article

Full-text available

Jan 2025

Recent years have seen extensive adoption of blockchain technology across a variety of application domains, all with the goal of enhancing data privacy, system trustworthiness, and security. One of the biggest problems with blockchain is its inability to scale; other problems include energy consumption, latency, throughput, and the ever-increasing volume of daily transactions. The consensus technique relies on hash functions, which are important to highlight. Thus, such development is fundamental to blockchain advances in terms of structure. This study introduces a revolutionary change to the Proof-of-Stake (POS) consensus methods by suggesting the replacement of the commonly used SHA256 hash function with the extremely efficient Blake3. Many blockchain-based systems, including POS algorithms, still employ the widely used SHA256 algorithm for cryptographic hashing. Nevertheless, fresh research has shown that SHA256 has performance and security flaws. We show that the Blake3 hash function, is better than the SHA256 hash in many respects, including latency, throughput, and energy, via rigorous testing and functional analysis. Diverse parameters were utilized, including the quantity of blocks and validators. Seen cases are taken into account for performance evaluation. In the initial scenario, utilizing 500 blocks and 4 validators, our proposed methodology has surpassed the benchmark by achieving a 66% reduction in latency, over 50% in throughput, and a 55% decrease in energy consumption. The rate of enhancement is nearly uniform across all other instances, indicating that the implementation of Blake3 within the conventional POS consensus mechanism has demonstrated its advantages.

The Impact of Artificial Intelligence in Enhancing the Performance of Blockchain Technology for the Services Sector Listed on the Amman Stock Exchange and Its Role in Achieving Sustainable Development Goals

Article

Full-text available

Feb 2025

Objective: investigate the impact of artificial intelligence in enhancing the performance of blockchain technology for the services sector listed on the Amman Stock Exchange, with the aim of Sustainable Development Goals. Theoretical Framework: The artificial intelligence helps in developing the performance of blockchain through technology, digital applications, hardware, software, databases, and communication networks. and This integration helps in achieving the sustainable development goals that work to improve the business environment, economic growth, and investment; support the digital economy, technological innovation. Method: The methodology adopted for this research comprises the descriptive approach. Data collection was carried out through 370 electronic questionnaires that were agreed to be completed by employees in a variety of Jordanian services sectors listed on the Amman Stock Exchange. Results and Discussion: The results obtained revealed that blockchain technology, in its aspects of decentralization, transparency, and traceability, is positively and statistically significantly affected by digital technology and applications. Research Implications: The practical and theoretical implications of this research are discussed, providing insights into how the results can be applied or influence practices in the field of Artificial Intelligence in Enhancing the Performance of Blockchain Technology and its Role in Achieving Sustainable Development Goals. These implications could encompass the services sector listed on the Amman Stock Exchange. Originality/Value: This study contributes to the literature by expanding the use of blockchain technology in government services, thus narrowing economic and social gaps and enhancing global cooperation to achieve the Sustainable Development Goals.

Blockchain ensuring academic integrity with a degree verification prototype

Article

Full-text available

Mar 2025

Blockchain technology has transformed information management through decentralization, security and immutability. However, a gap persists in its application for the issuance and verification of professional qualifications in education. This study presents a prototype developed in Python and Docker, designed to guarantee the authenticity and traceability of academic credentials through a hybrid blockchain network with six Docker nodes. The prototype includes processes such as initial data registration, node configuration, credential generation with QR codes and associative signature based on Byzantine consensus. During the signing stage, previously stored records are validated and authenticated, ensuring integrity before final credentials are generated. The peer-to-peer network ensures synchronization, decentralized storage and immutability of records. On average, initial title registration on the blockchain took 2.97 s, with block replication taking 0.02 s. Record signing had a latency of 0.96 s, with replication in 0.79 s, and Byzantine consensus took 0.12 s, all with moderate resource consumption. The generated titles, verifiable via QR codes, reinforce trust and reduce academic fraud. This model stands out for its practical and scalable approach, with potential for adaptation to other sectors. Future work should address the scalability and robustness of the system for more complex applications.

Aplicação da Tecnologia Blockchain no Processo de Desenvolvimento de Produtos: Abordagem Inicial para uma Revisão Sistemática da Literatura

Chapter

Jan 2025

Blockchain for Hardware Security and Trust

Chapter

Mar 2025

The chapter delves into the innovative fusion of blockchain technology and hardware security, unveiling a symbiotic relationship that promises to redefine trust and fortify digital ecosystems. In a rapidly evolving digital landscape, security and trust are paramount, and this chapter illuminates how blockchain technology contributes significantly to achieving these objectives. Blockchain’s core principles, including decentralization, immutability, and consensus mechanisms, serve as robust foundations for enhancing hardware security. By integrating blockchain into hardware systems, trust can be established through transparent, tamper-resistant ledgers that validate and authenticate hardware components. This trust is pivotal for safeguarding a wide array of applications, from securing Internet of Things (IoT) devices to bolstering supply chain integrity. The chapter also explores the practical implementation of blockchain within hardware security, highlighting cryptographic innovations and privacy-preserving protocols. Additionally, it delves into the benefits of leveraging smart contracts for automating and securing hardware-related transactions and processes. This exploration offers valuable insights and a roadmap for engineers, researchers, and cybersecurity professionals, enabling them to harness the full potential of blockchain technology to create more trustworthy and secure hardware systems. By embracing blockchain, we open doors to a future where hardware security and trust are fortified, setting the stage for the continued advancement of digital technology with confidence and resilience.

An Efficient Data Mining Technique for Assessing Satisfaction Level With Online Learning for Higher Education Students During the COVID-19

Article

Full-text available

Jan 2022

All the educational organizations mainly aim at elevating the academic performance of students for improving the overall quality of education. In this direction, Educational Data Mining (EDM) is a rapidly trending research area that utilizes the essence of Data Mining (DM) concepts to help academic institutions figure out useful information on the Student Satisfaction Level (SSL) with the Online Learning process (OL) during COVID-19 lock-down. Different practices have been tried with EDM to predict students’ behaviors to reach the best educational settings. Therefore, Feature Selection (FS) is typically employed to find the most relevant subset of features with minimum cardinality. As the predictive accuracy of a satisfaction model is significantly influenced by the FS process, the effectiveness of the SSL model is elaborately studied in this paper in connection with FS techniques. In this connection, a dataset was first collected online via a questionnaire of student reviews on OL courses. Using this datatset, the performance of wrapper FS techniques in DM and classification algorithms was analyzed in terms of fitness values. Ultimately, the goodness of subsets with different cardinalities is evaluated in terms of prediction accuracy and number of selected features by measuring the quality of 11 wrapper-based FS algorithms and the k-Nearest Neighbor (k-NN) and Support Vector Machine (SVM) as base-line classifiers. Based on the experiments, the optimal dimensionality of the feature subset was revealed, as well as the best method. The findings of the present study evidently support the well-known conjunction of the existence of minimum number of features and an increase in predictive accuracy. It is remarkable the relevancy of FS for high-accuracy SSL prediction, as the relevant set of features can effectively assist in deriving constructive educational strategies. Our study contributes a feature size reduction of up to 80% along with up to 100% classification accuracy on the adopted real-time dataset.

IoT Workflow Scheduling Using Intelligent Arithmetic Optimization Algorithm in Fog Computing

Article

Full-text available

Dec 2021
Comput Intell Neurosci

Instead of the cloud, the Internet of things (IoT) activities are offloaded into fog computing to boost the quality of services (QoSs) needed by many applications. However, the availability of continuous computing resources on fog computing servers is one of the restrictions for IoT applications since transmitting the large amount of data generated using IoT devices would create network traffic and cause an increase in computational overhead. Therefore, task scheduling is the main problem that needs to be solved efficiently. This study proposes an energy-aware model using an enhanced arithmetic optimization algorithm (AOA) method called AOAM, which addresses fog computing’s job scheduling problem to maximize users’ QoSs by maximizing the makespan measure. In the proposed AOAM, we enhanced the conventional AOA searchability using the marine predators algorithm (MPA) search operators to address the diversity of the used solutions and local optimum problems. The proposed AOAM is validated using several parameters, including various clients, data centers, hosts, virtual machines, tasks, and standard evaluation measures, including the energy and makespan. The obtained results are compared with other state-of-the-art methods; it showed that AOAM is promising and solved task scheduling effectively compared with the other comparative methods.

Is blockchain able to enhance environmental sustainability? A systematic review and research agenda from the perspective of Sustainable Development Goals (SDGs)

Article

Full-text available

Sep 2021

Blockchain is a disruptive technology that is revolutionizing information technology and represents a change of cultural paradigm for the way in which information is shared. Companies are rushing to understand how they can use blockchain distributed ledger technology to innovate processes, products and transactions. In a globalized world where environmental sustainability is a critical success factor, what is the role of the blockchain? By using a systematic review approach and the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) protocol, this study attempts to identify whether and how blockchain technology is considered able to affect environmental sustainability. Findings from 195 studies from 2015 to 2020 were analysed after the search protocol was applied. The results indicate that blockchain technology could contribute to environmentally sustainable development goals (SDGs) from different points of view, such as supporting the realization of a sustainable supply chain, improving energy efficiency and promoting the creation of secure and reliable smart cities. Furthermore, the investigation highlights the sectors where to focus research investments, providing a way to reward sustainable behaviour and increasing environmental sustainability. On the other hand, blockchain has no negligible negative effects on the environment that need to be considered before adoption.

Intelligent workflow scheduling for Big Data applications in IoT cloud computing environments

Article

Full-text available

Dec 2021
CLUSTER COMPUT

Effective task scheduling is recognized as one of the main critical challenges in cloud computing; it is an essential step for effectively exploiting cloud computing resources, as several tasks may need to be efficiently scheduled on various virtual machines by minimizing makespan and maximizing resource utilization. Task scheduling is an NP-hard problem, and consequently, finding the best solution may be difficult, particularly for Big Data applications. This paper presents an intelligent Big Data task scheduling approach for IoT cloud computing applications using a hybrid Dragonfly Algorithm. The Dragonfly algorithm is a newly introduced optimization algorithm for solving optimization problems which mimics the swarming behaviors of dragonflies. Our algorithm, MHDA, aims to decrease the makespan and increase resource utilization, and is thus a multi-objective approach. β-hill climbing is utilized as a local exploratory search to enhance the Dragonfly Algorithm’s exploitation ability and avoid being trapped in local optima. Two experimental studies were conducted on synthetic and real trace datasets using the CloudSim toolkit to compare MHDA to other well-known algorithms for solving task scheduling problems. The analysis, which included the use of a t-test, revealed that MHDA outperformed other well-known algorithms: MHDA converged faster than other methods, making it useful for Big Data task scheduling applications, and it achieved 17.12% improvement in the results.

Decentralized Autonomous Organization

Article

Full-text available

Apr 2021

A DAO is a blockchain-based system that enables people to coordinate and govern themselves mediated by a set of self-executing rules deployed on a public blockchain, and whose governance is decentralised (i.e., independent from central control).

Reptile Search Algorithm (RSA): A nature-inspired meta-heuristic optimizer

Article

Nov 2021
EXPERT SYST APPL

This paper proposes a novel nature-inspired meta-heuristic optimizer, called Reptile Search Algorithm (RSA), motivated by the hunting behaviour of Crocodiles. Two main steps of Crocodile behaviour are implemented, such as encircling, which is performed by high walking or belly walking, and hunting, which is performed by hunting coordination or hunting cooperation. The mentioned search methods of the proposed RSA are unique compared to other existing algorithms. The performance of the proposed RSA is evaluated using twenty-three classical test functions, thirty CEC2017 test functions, ten CEC2019 test functions, and seven real-world engineering problems. The obtained results of the proposed RSA are compared to various existing optimization algorithms in the literature. The results of the tested three benchmark functions revealed that the proposed RSA achieved better results than the other competitive optimization algorithms. The results of the Friedman ranking test proved that the RSA is a significantly superior method than other comparative methods. Finally, the results of the examined engineering problems showed that the RSA obtained better results compared to other various methods.

A systematic review of blockchain scalability: Issues, solutions, analysis and future research

Article

Oct 2021

Blockchain is an inspiring emerging technology that takes much attention from various researchers and companies. The technology offers various benefits such as data security, autonomy, immutability, transparency, and auditability. Hence, blockchain is getting large adoptions for various applications besides cryptocurrencies. Despite these benefits, scalability is a big challenge to blockchain impeding its mainstream adoption. This paper gives a systematic review of blockchain scalability. We follow a systematic process to investigate the research trend on blockchain scalability and review its state of the art. We review the various proposed solutions and methods for blockchain scalability. We also review the performance analysis of blockchain systems. We assess the proposed scalability solutions, deduce future research directions on the blockchain scalability, and finally discuss the blockchain adoption. We hope this paper will serve as a guide for learning and research on blockchain scalability.

Applications, Deployments, and Integration of Internet of Drones (IoD): A Review

Article

Sep 2021

The Internet of Drones (IoD) has become a hot research topic in academia, industry, and management in current years due to its wide potential applications, such as aerial photography, civilian, and military. This paper presents a comprehensive survey of IoD and its applications, deployments, and integration. We focused in this review on two main sides; IoD Applications include smart cites surveillance, cloud and fog frameworks, unmanned aerial vehicles, wireless sensor networks, networks, mobile computing, and business paradigms; integration of IoD includes privacy protection, security authentication, neural network, blockchain, and optimization based-method. A discussion highlights the hot research topics and problems to help researchers interested in this area in their future works. The keywords that have been used in this paper are Internet of Drones.

"Blockchain and Land Administration"

Book

Jan 2018

Advanced optimization technique for scheduling IoT tasks in cloud-fog computing environments

Article

May 2021
FUTURE GENER COMP SY

Cloud-fog computing frameworks are emerging paradigms developed to add benefits to the current Internet of Things (IoT) architectures. In such frameworks, task scheduling plays a key role, and the optimized schedule of IoT task requests can improve system performance and productivity. In this paper, we developed an alternative task scheduling technique for IoT requests in a cloud-fog environment based on a modified artificial ecosystem-based optimization (AEO), called AEOSSA. This modification is developed using the operators of the Salp Swarm Algorithm (SSA) in an attempt to enhance the exploitation ability of AEO during the process of finding the optimal solution for the problem under consideration. The performance of the designed AEOSSA approach to tackling the task scheduling problem is evaluated using different synthetic and real-world datasets of different sizes. In addition, a comparison is conducted between AEOSSA and other well-known metaheuristic methods for performance investigation. The experimental results demonstrate the high ability of AEOSSA to tackle the task scheduling problem and perform better than other methods according to the performance metrics such as makespan time and throughput.