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Exploring the Potential of Blockchain Technology in an IoT-Enabled Environment: A Review

January 2024
IEEE Access PP(99):1-1

DOI:10.1109/ACCESS.2024.3366656

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Authors:

Preeti Gulia

Maharshi Dayanand University

Nasib Singh Gill

M D University Rohtak, Haryana, India

Mohammad Yahya

Oakland University

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Internet of Things (IoT) plays an essential contribution in connecting devices and enabling seamless data exchange, leading to increased efficiency and convenience. However, security concerns in IoT systems are significant, as compromised devices can lead to data breaches and privacy violations. Blockchain technology can enhance IoT security by providing decentralized consensus, immutability, and transparent transaction records, ensuring secure and trustworthy communication and data integrity. This review article gives a succinct but thorough understanding of blockchain technology, covering architecture of blockchain, working principles, types, applications, platforms, and its role in the IoT environment. The study highlights potential benefits of blockchain like enhanced security and privacy, and explores its integration with IoT. Additionally, the study discusses various real-world applications, examines blockchain platforms, and addresses the limitations and challenges associated with blockchain technology. This review serves as a valuable resource for researchers and practitioners seeking a deeper understanding of blockchain’s potential and its implications in the IoT landscape.

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Exploring the Potential of Blockchain

Technology in an IoT-Enabled Environment: A Review

Deepak1, Preeti Gulia1, Nasib Singh Gill1, Mohammad Yahya2, Punit Gupta3, Prashant Kumar Shukla4, Piyush Kumar Shukla5

1Department of Computer Science & Applications, Maharshi Dayanand University, Rohtak, India

2Computer Science, Oakland University, Rochester Hills, Michigan, United States

3School of Computer Science, University College Dublin, Dublin, Ireland, D04 V1W8

4Department of Computer Science and Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur - 522302, Andhra Pradesh, India,

5Department of Computer Science & Engineering, UIT-RGPV, Bhopal, Madhya Pradesh, India, PIN: 462033

Corresponding author: Punit Gupta (punit.gupta@ucd.ie)

ABSTRACT Internet of Things (IoT) plays an essential contribution in connecting devices and enabling seamless data exchange,

leading to increased efficiency and convenience. However, security concerns in IoT systems are significant, as compromised

devices can lead to data breaches and privacy violations. Blockchain technology can enhance IoT security by providing

decentralized consensus, immutability, and transparent transaction records, ensuring secure and trustworthy communication and

data integrity. This review article gives a succinct but thorough understanding of blockchain technology, covering architecture of

blockchain, working principles, types, applications, platforms, and its role in the IoT environment. The study highlights potential

benefits of blockchain like enhanced security and privacy, and explores its integration with IoT. Additionally, the study discusses

various real-world applications, examines blockchain platforms, and addresses the limitations and challenges associated with

blockchain technology. This review serves as a valuable resource for researchers and practitioners seeking a deeper understanding

of blockchain's potential and its implications in the IoT landscape.

INDEX TERMS Blockchain, Data Exchange, Internet of Things (IoT), Privacy, Security.

I. INTRODUCTION

The advent of IoT has revolutionized the environment by

connecting devices and enabling seamless communication and

data exchange. A network of interconnected devices and

sensors operating in an internet-based environment is known as

an IoT-based environment [181]. These devices, equipped with

sensors and software, interact with their surroundings and each

other. The layered structure of IoT includes perception,

network, middleware, application, business, and security layers

[182]. Data is collected from the physical environment at the

perception layer, and communication between devices happens

at the network layer using technologies like Wi-Fi or cellular

networks. The middleware layer handles data processing and

management, while the application layer delivers services to

end-users. The business layer focuses on integration with

existing systems, and the security layer is crucial for protecting

data and devices from unauthorized access and attacks [151].

IoT security concerns include firmware vulnerabilities, weak

authentication, and insufficient data encryption. Notable IoT

attacks include the Denial of service (DDoS) attacks, phishing,

spoofing, and data thefts [78][79] [158]. The taxonomy of the

security threats in IoT is illustrated in figure 1. Protecting IoT

environments requires robust security measures like

encryption, secure authentication, regular updates, and

vulnerability testing. However, this increased connectivity also

poses significant security concerns. Figure 2. illustrates the

increasing number of IoT devices, cyber-attacks year after

year. These attacks exploit vulnerabilities in IoT systems,

leading to data breaches, privacy violations, and even physical

damage. The solutions based on blockchain technology are

promising for boosting the security of IoT-enabled

environments.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

FIGURE 1. Security Threats in IoT[158]

By leveraging blockchain in IoT, organizations can enjoy

several benefits. Firstly, it establishes a trust layer among

devices, enabling secure and direct peer-to-peer transactions

without relying on intermediaries. Secondly, blockchain

enhances data integrity and privacy, ensuring that IoT data is

not compromised or altered maliciously. Last but not least, the

decentralized nature of blockchain reduces single points of

failure and increases system resistance to cyberattacks,

constructing more robust and secure IoT environments. The

review paper is organized into six sections as depicted in

Figure. 3.

FIGURE 2. Annual number of IoT attacks (worldwide) [9]

The significance and applicability of blockchain technology are

discussed in the first part. The second section performs

statistical analysis using the Scopus and Web of Science

database. The third section offers an overview of blockchain,

covering its architecture, working principles, different types,

and its diverse platform applications. The fourth segment

explores how blockchain and IoT work together, exploring the

synergies and potential applications in this domain. The fifth

segment critically discussed blockchain technology's

drawbacks and difficulties. The final section discusses

conclusion and potential future study areas that could help solve

the problems and further the potential of blockchain

technology. The objective of this study is to update the literature

significantly through a thorough grasp of blockchain

technology and how it affects various industries.

FIGURE 3. Sections of this study

In the realm of Blockchain and IoT integration, this paper is a

comprehensive exploration into the potential of these

technologies, specifically highlighting their impact on

connectivity, security, and data management. Our focus is on

unraveling the intricate dynamics that unfold when Blockchain

meets IoT, offering valuable insights to researchers,

practitioners, and industry stakeholders navigating this

transformative fusion. The paper addresses critical issues

within the IoT ecosystem, including security vulnerabilities,

data integrity, and trust. As we embark on this exploration, the

profound implications extend beyond technological

advancements, shaping industries, societies, and economies

globally. This research significantly contributes to the growing

body of knowledge steering the future of technology.

II. OVERVIEW OF BLOCKCHAIN

Blockchain is a trending sector now-a-days firstly

conceptualized by an anonymous person or group known as

“Satoshi Nakamoto”. Blockchain gained popularity from its

very first application cryptocurrency which was termed as

“Bitcoin” [183]. However, blockchain is a digital ledger similar

to bank ledger but with some additional characteristics like

“Decentralization” and “Distributed”[6]. With the advancement

of technologies, a large portion of the population is affected by

the cyber-attacks, in which the financial cyber-attacks are most

common. Therefore, blockchain produced tremendous results

for enhancing transaction security. Blockchain enables the

secure and efficient exchange of digital assets and other forms

of data without the need for a centralized intermediary [6].

Blockchain operates through the use of some key technologies

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

like hashing, consensus, cryptography, and distributed ledger

technology (DLT) [10].

Such technologies will enable blockchain to some prominent

features like decentralization, immutable, security, privacy and

trust etc. The technology is now being used to facilitate secure

transactions in areas such as finance, healthcare, government,

and other industries [68]. For example, blockchain is being used

to create smart contracts, manage supply chain activities, and

for digital identity verification. Also, blockchain technology

contains some limitations like scalability, cost, regulation etc.

[1][2].

• RELATED WORK: A thorough review of IoT security

intelligence is given by Sarker et al. (2023) [159], with an

emphasis on machine learning solutions. Sisodia et al. (2023)

[160] explores the issues and future potential associated with

security risks associated with IoT. In their investigation of the

application of blockchain to V2X communications, Rao et al.

(2023) [161] highlight security concerns and the need of

integrating blockchain with IoT for safe data management. In

order to increase security and privacy in small and medium-

sized businesses, Khan et al. (2023)[162] provide a cooperative

framework combining blockchain, AI, and IoT. The framework

shows gains in efficiency, security, and data management. In

their discussion of blockchain's applicability in IoT-enabled

healthcare, Singh et al. (2023) [163] address security issues and

stress the importance of trustworthy authentication methods. In

order to identify gaps and future issues, Zubaydi et al. (2023)

[164] conducted a systematic literature analysis on using

blockchain technology to enhance security and privacy in the

Internet of Things. The study conducted by Wenhua et al.

(2023) [165] delves into the topics of blockchain technology

security, healthcare applications, problems, and future trends.

Blockchain applications in waste management are examined by

Jiang et al. (2023) [166], who provide an overview, difficulties,

and potential. In order to secure IoT-based healthcare

multimedia data, Karthik et al. (2023) [167] present deep

intelligent blockchain technology, highlighting the deep

learning and blockchain integration for improved security. This

thorough synthesis advances our understanding of the

opportunities and difficulties presented by the convergence of

blockchain and IoT in a variety of fields.

The taxonomy of blockchain as shown in Figure 4. helps

to classify the different aspects of blockchain and its various

use cases. The taxonomy includes its architecture, types,

characteristics, applications and platforms [152].

FIGURE 4. Taxonomy of Blockchain [152].

A. BLOCKCHAIN ARCHITECTURE

As seen in Figure 5, a blockchain system with multiple tiers,

each serving a specific purpose, is known as a layered

architecture. The application layer, consensus layer, network

layer, data layer, and hardware layer are the traditional layers

that work together to provide a safe and decentralized

blockchain transaction structure [153]. Together, these layers

allow for decentralized and safe blockchain transactions. The

application layer functions as an interface between users and

the blockchain, offering a front-end interface for using features

like sending and receiving money via apps like bitcoin wallets

[3]. The smart contract is self-executing programs that enforce

predefined conditions and automate transactions based on

agreements between parties. Smart contracts eliminate

intermediaries and find applications in several areas such as

transactions, supply chains, and real estate [3]. The consensus

layer permits the inclusion of new blocks by employing

methods such as Proof of Work [1] and Proof of Stake [23] to

reach consensus among network nodes regarding the state of

the blockchain [5][6]. The network layer controls

communication and upholds data integrity while ensuring

smooth data transmission between nodes in the blockchain

network [4].

FIGURE 5. Architecture of Blockchain [153].

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

The storage layer stores data, including blocks, smart contracts

and transactions which are replicated over the network for

availability and security. Components such as block headers,

Merkle Trees, and Nonce contribute to the security and

transparency of the blockchain [1][2]. These layers and

components play crucial roles in blockchain technology, which

has seen accelerated development due to the growth of the

cryptocurrency industry and the rise of distributed ledger

technology [7][8].

1) APPLICATION LAYER

This layer serves as the highest-level interface that enables user

interaction and provides a front-end interface for accessing the

blockchain for example, a common application that

communicates with the blockchain to transmit and receive

money is a bitcoin wallet [3]. This specific layer has been given

the important task of carrying out the complex logic and

regulations relevant to smart contracts on the blockchain.

• SMART CONTRACT: A "smart contract" is a self-

executing programme that automatically carries out the terms

of an agreement between two parties. One possible application

for a smart contract would be to automate the fulfillment of a

financial transaction according to preset standards [3]. Smart

contracts have applications in many different areas, such as real

estate, mortgages, and supply chains. Smart contracts are

essential for facilitating automated agreements and

transactions, eliminating the need for intermediaries. IoT

devices can independently respond to specified conditions and

rules programmed in the contract by altering energy usage in a

smart home setting using real-time data from devices such as

smart meters and thermostats. Moreover, smart contracts enable

trustless transactions among IoT devices, guaranteeing secure

exchanges of data or assets without the need for third-party

verification. This is a notable benefit in diverse IoT ecosystems.

In addition, smart contracts assure unchangeable record-

keeping by documenting all transactions and agreements on a

blockchain, providing a clear record of ledger activity and

ensuring the integrity and ability to be audited, which are

essential characteristics for IoT applications.Smart contracts

play a crucial role in supply chain management by automating

interactions between stakeholders and IoT devices to guarantee

transparency and traceability. For example, in the field of

agriculture, they monitor the entire journey of product from the

farm to the table. In the transportation sector, they use IoT

sensor data to automatically manage vehicle rentals. Smart

contracts in smart grids enable direct energy trading between

IoT devices, hence enhancing efficiency and increasing the

integration of renewable energy sources[22][121]. Smart

contracts are becoming more and more popular because of their

remarkable capacity to simplify complex transactions and do

away with the need for middlemen. It is possible to construct

and execute smart contracts on platforms like Polkadot [11],

Hyperledger [70], and Ethereum [22].

2) CONSENSUS LAYER

This layer allows the addition of new blocks to the chain and

achieving network-wide consensus over the status of the

blockchain. Different consensus methods, like Proof of Work

or Proof of Stake, are employed to achieve this [5] [6]. When it

comes to verifying the integrity of anonymous individuals

adding transactions, blockchain's desirable characteristic of

anonymity presents a hurdle. This issue is fixed by verifying

each transaction and putting it in a block. After that, the choice

of whether to include a block in the blockchain is made using

consensus mechanisms. Every blockchain transaction is based

on a consensus algorithm. Table 1 lists a variety of distinct

consensus mechanisms created especially for blockchains,

including Proof of Work (PoW) [1], Proof of Stake (PoS) [23],

Delegated Proof of Stake (DPoS) [25], Practical Byzantine

Fault Tolerance (PBFT) [32], Directed Acyclic Graph (DAG)

[29], and Proof of Authority (PoA) [27]. The most popular

consensus algorithms are PBFT, PoW, PoS, DPoS, and DAG,

while DAG is the most unique. In PoW, an issue that requires a

lot of time and electricity to solve is solved by randomly

guessing nonce values.

a: PROOF-OF-WORK

A consensus method known as Proof of Work (PoW) requires

users, or miners, to solve difficult computational problems in

order to approve transactions and append new blocks to the

blockchain. PoW is a consensus method that consumes a

significant amount of energy and computing resources.

Gupta et al. [12] proposed that blockchain is a constantly

evolving technology that underlies Bitcoin and has already been

widely implemented. The advent of cryptocurrency and

blockchain has given rise to a new decentralized security and

trust paradigm through the consensus system. To make

blockchain more useful and efficient, there are still a lot of

unresolved problems that require research. Based on various

levels of difficulty and mining rate, the Proof-of-Work (PoW)

algorithm's performance is assessed in this study. Organizations

can adjust difficulty levels depending on their business

requirements, but higher difficulty levels require more

resources and energy consumption. High difficulty levels

should not be mined on standard machines, and PoW may not

be appropriate for businesses with tight budgets and schedules.

Other consensus methods, such as Practical Byzantine Fault

Tolerance or Proof-of-Stake, may be more applicable.

Lasla et al. [13] presented a new energy-efficient consensus

method for public blockchains dubbed Green-PoW, which uses

up to 50% less energy overall during mining than the original

Proof-of-Work algorithm. Time is divided into epochs by

Green-PoW, which has two rounds of mining. The first round

is comparable to the original PoW, while the second round is

just for the miners who were chosen in the first round. The

effectiveness of Green-PoW was validated through extensive

simulations, and the findings reflect significant energy savings

while keeping important security characteristics including

lowering fork occurrences and mining centralization.

b: PROOF-OF-STAKE

Using less energy than Proof of Work (PoW)[1], Proof of Stake

(PoS)[23] is a consensus technique that enables validators to

produce new blocks and validate transactions. The quantity of

coins that validators are willing to "stake" as collateral

determines which ones they are selected for.Staking involves

participants locking up a certain amount of cryptocurrency as

collateral. Validators are chosen to create new blocks

proportionate to the stakes they have in the cryptocurrency;

these validators suggest and approve transactions, and

consensus is reached when a supermajority of participants agree

to a new block. The validated block is then added to the

blockchain, and the validator who made the proposal is

rewarded. Unlike Proof-of-Work, PoS is purposefully made to

use less energy, encouraging long-term cryptocurrency holding

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

as a way to influence the consensus process. In addition, Proof

of Stake (PoS) employs measures to discourage malevolent

conduct by levying fines or reducing a validator's stake for

participating in such actions [168].

The authors of the study [14] predict that proof-of-stake

designs will overtake proof-of-work designs as a more

competitive type of peer-to-peer cryptocurrency after their

design has been validated in the market. This is because there

is no longer a reliance on energy use, which lowers inflation

and transaction costs while keeping a similar level of network

security.

Ge et al. [15] focused on the blockchain consensus

algorithm, with a focus on enhanced proof-of-stake (PoS)

algorithms. Based on the selection of block producers, the

distribution of rewards, and the incentive mechanisms, the

algorithms are divided into three groups. The analysis of four

particular algorithms includes a summary of their improvement

plans, outcomes, benefits, and drawbacks. These changes are

primarily intended to address the issues of choosing block

producers, distributing block rewards fairly, and increasing

consensus efficiency while maintaining privacy and security.

According to the study, algorithm changes should take into

account how to keep the blockchain decentralized while

maintaining the consensus without going against the established

rules. A consensus method based on an incentive mechanism is

intended to be created in order to fairly distribute block rewards

while preventing network security issues.

c: PROOF OF AUTHORITY

Proof Of Authority (PoA) is a consensus process where block

validators are pre-selected and known identities on a

permissioned blockchain, relying on their reputation and

authority to validate transactions, offering high throughput and

quicker confirmation times.

For blockchain systems to be secure and reliable, especially

in permissioned networks, the principles of blockchain-oriented

software engineering are crucial. In order to increase security

and confidentiality, Nazir et al. [16] presented a dual blockchain

system that has special components like dual-sided architecture

and consensus algorithms. The suggested technique is

anticipated to improve validators' single node dependability

while enhancing the network's overall security and

confidentiality.

Joshi et al. [17] presented a thorough overview of

blockchain networks' proof of authority (PoA) consensus

algorithm. Due to its high throughput and scalability, PoA is

regarded as a viable replacement for PoW and PoS. This is

because it is appropriate for Decentralized Applications (DApp)

development, private blockchains, and notary-based

applications that demand trust in validators. Its appropriateness

for decentralized public blockchain networks like

cryptocurrency has not yet been established. Despite this, PoA's

performance and cost-effectiveness make it a viable rival to

established consensus algorithms and a promising blockchain

option for exclusive or restricted blockchain networks.

d: BYZANTINE-FAULT-TOLERANT (BFT)

BFT is a consensus algorithm that ensures consensus among

participants in the presence of Byzantine faults, such as

arbitrary failures or attacks, allowing a distributed system to

function correctly and come to agreement even when some

nodes are malicious or defective. Practical Byzantine Fault

Tolerance (PBFT) and Tendermint are two examples of BFT

implementations.With a primary application in permissioned

blockchain networks, Practical Byzantine Fault Tolerance

(PBFT) is a consensus algorithm designed to guarantee fault-

tolerant consensus in distributed systems where nodes may

display malevolent behavior or experience breakdowns. There

are multiple crucial steps in the protocol: A new block or

transaction is proposed by a client to the primary node, which

then sends the proposed block to all nodes for validation along

with the primary node's digital signature. Nodes broadcast

prepare messages in response to pre-prepare messages,

indicating that the proposed block has been validated; nodes

broadcast commit messages in response to prepare messages

from a 2/3 majority of nodes, including itself; and nodes

respond to the client after receiving commit messages from a

2/3 majority, indicating that the transaction or block has been

committed. PBFT works best in permissioned networks with

fixed and known participants, assuming that less than one-third

of nodes are malevolent. Prominent for its low latency and great

throughput, PBFT is useful for applications that need quick

finality[169].

Castro et al. [18] provided a novel state-machine replication

technique with a large performance gain over existing

algorithms, the ability to handle Byzantine faults, and the ability

to operate in asynchronous systems. Additionally, the authors

discuss BFS, a Byzantine-fault-tolerant implementation of NFS

that, thanks to improvements like message authentication codes

and incremental checkpoint-management strategies, performs

nearly as well as an unreplicated service. Byzantine-fault-

tolerant algorithms are crucial because they can keep systems

operating normally even in the presence of software defects. By

lowering the number of replicas and copies of the state, the

authors hope to lower the amount of resources needed to

implement their algorithm.

Coelho et al. [19] focused on the dBFT consensus of the Neo

Blockchain, one of numerous PBFT-inspired blockchain

implementations. The first and second generations of the dBFT

consensus (dBFT 1.0 and 2.0) are compared, and improvements

for the second generation (dBFT 2.0+) are introduced, such as

the inclusion of proofs during change views to prevent isolated

committed nodes. Also, the study proposes a third generation

with multiple block proposals (dBFT 3.0), which would

incorporate a further consensus negotiation step. Additionally,

covered are blacklisting strategies that could fend off Byzantine

attackers. The authors' backgrounds range from applied

computer scientists to experts in game theory, optimization, and

cryptography.

Christofi et al. [20] proposed an extensive understanding of

blockchain technology, including its architecture and several

consensus protocols. The primary objective is to augment the

DBFT algorithm by creating a reputation mechanism to

increase the protocol's fairness and security. Without the

involvement of third parties, the blockchain technology enables

direct asset transfers between peers and offers security and

trust. The DBFT algorithm is one of the most promising and fair

consensus protocols due to its democratic implementation

through the voting procedure. The improvement of the DBFT

algorithm addressed the limitation of lack of interest of ordinary

nodes to vote out for misbehaved nodes and ensured the

malicious nodes lost all their rights in the network. While the

improvement was theoretical, future work includes practical

implementation to see the behavior and results of the system in

real conditions and development of the reputation mechanism

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

to examine its behavior based on the formulas and measurement

categories.

Angelis et al. [21] compared PBFT to Aura and Clique, two

PoA-based consensus algorithms for permissioned blockchains,

in terms of consistency, availability, and performance. In

contrast to PBFT, which maintains the blockchain's consistency

at the expense of availability and is preferable when data

integrity is a priority, the study asserts that PoA algorithms can

compromise consistency for availability when taking into

account the presence of Byzantine nodes. The study comes to

the conclusion that while PoA algorithms perform better, the

gains in PBFT's consistency guarantees can compensate for the

loss of consistency guarantees. To support their assertions and

define a framework for comparing and assessing permissioned

blockchains, the authors intend to carry out additional research

and testing.

e: Directed Acyclic Graphs (DAG)

Consensus techniques based on Directed Acyclic Graphs

(DAGs), such as Tangle, which is employed by IOTA, take

advantage of a graph topology in which two transactions

directly support one another. A DAG structure is formed by

other nodes validating and confirming the linked transactions

after users choose two unconfirmed transactions (tips) for

validation and generate a new transaction approving them. The

protocol proceeds in multiple steps. As more transactions

reference a particular one, it receives confirmation and gains

weight that influences subsequent validations. This way,

consensus is dynamically reached as the network grows. High

scalability is prioritized in DAG-based systems, which also do

away with the requirement for miners or validators. This

enables asynchronous confirmation and possibly speedier

consensus. IOTA uses the Tangle protocol in particular because

it allows for free microtransactions, which is ideal for Internet

of Things (IoT) devices. Ultimately, each consensus algorithm

addresses different objectives and difficulties; the selection of

an algorithm depends on the particular needs of the blockchain

network in question. Examples of these algorithms include

PBFT for fault tolerance, PoS for energy efficiency, and DAG

structures for scalability [29] [170]. Table 1. presents a

comprehensive comparison of consensus protocols.

When it comes to energy efficiency for IoT devices,

consensus algorithms such as Proof of Stake (PoS) [23][24] and

Delegated Proof of Stake (DPoS)[25] reduce energy usage by

using stakeholder voting instead of resource-intensive mining.

Lightweight consensus algorithms like Practical Byzantine

Fault Tolerance (PBFT)[32][33] and Directed Acyclic Graphs

(DAGs)[29] are used to assure effective functioning of

hardware-constrained IoT devices while preserving

computational resources. These consensus methods provide

customized solutions to improve energy consumption, adapt to

hardware limitations, and guarantee fast transaction rates in IoT

contexts.

TABLE 1 Comparison of Consensus Protocol

Consensus

Protocol

Type of

Blockchain

Transaction

Rate

Cost of

Participatio

Scalability

Latency

Throughput

Examples/

Applications

References

Proof of Work

(PoW)

Permissionless

Low to

Moderate

High

Low to

Medium

High

Moderate

Bitcoin,

Ethereum

[1][22]

Proof of Stake

(PoS)

Permissionless

/Permissioned

Moderate to

High

Low to High

High

Low to

High

Cardano,

Tezos

[23][24]

Delegated

Proof of Stake

(DPoS)

Permissionless

High

Moderate

High

Low

High

EOS, TRON

[25]

Leased Proof

of Stake

(LPoS)

Permissionless

Moderate

Low to

Moderate

High

Low

High

Waves

[26]

Proof of

Authority

(PoA)

Permissioned

High

Low to

Moderate

High

Low

High

Ethereum

(private

networks)

[27]

Proof of

Importance

(PoI)

Permissioned/Per

missionless

Moderate to

High

Low to

Moderate

High

Low

High

NEM

[28]

Directed

Acyclic Graph

(DAG)

Permissionless/P

ermissioned

High

Low to

Moderate

High

Low

High

IOTA, Nano

[29]

Byzantine

Fault

Tolerance

(BFT)

Permissioned/Per

missionless

Moderate to

High

Moderate

Low to

Medium

High

Ripple,

Stellar

[30][31]

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

Practical

Byzantine

Fault

Tolerance

(pBFT)

Permissioned

High

Low to

Medium

High

Hyperledger

Fabric,

Tendermint

[32][33]

Delegated

Byzantine

Fault

Tolerance

(dBFT)

Permissioned

High

Moderate

Low to

Medium

High

NEO

[34]

Proof of

Capacity

(PoC)

Permissioned

Low to

Moderate

Low to

Moderate

High

Low to

Medium

Moderate

Burst, Storj

[35][36]

Proof of

Activity (PoA)

Permissioned

High

Low to

Moderate

High

Low

High

Decred,

Komodo

[37][38]

Proof of

Elapsed Time

(PoET)

Permissioned

Moderate

Low to

Moderate

High

Low

High

Hyperledger

Sawtooth

[39]

3) NETWORK LAYER

The maintenance and seamless transmission of data between

the nodes within the blockchain network are entrusted to this

particular layer. It manages the communication between nodes

and ensures the integrity of the data being transmitted [4].

Confirmation latency, the time between broadcast and

confirmation of a transaction, is a critical performance indicator

for blockchain. The propagation latency of messages via the

peer-to-peer (P2P) network determines the lower bound of

confirmation latency. De facto peer-to-peer protocols, like the

one used by Bitcoin, rely on random connections, in which each

node links to a random selection of nodes. By removing a single

point of weakness, cutting out middlemen lowers transaction

costs and improves security. However, the restricted ability to

scale and the higher risk of Sybil attacks are drawbacks of this

approach [40].

4) STORAGE LAYER

The storage layer in blockchain architecture refers to the

component responsible for securely storing and organizing the

data within the blockchain network, ensuring its immutability

and accessibility for all participants.

a: DISTRIBUTED LEDGER TECHNOLOGY

Distributed ledger technology (DLT), is a system for storing

and distributing data among several ledgers that is still in

development [4]. It prevents double spending and allows peer-

to-peer asset ownership transfers without the need for a central

record-keeper. However, some of its disadvantages include

scalability, performance difficulties, and significant energy

usage. DLT's transparency and auditability enhance trust

among parties [41].

b: Hashing

A hash is a mathematical operation that converts inputs of

arbitrary size into encrypted outputs of a specific size [95].

Since it is a one-way process, the hash cannot be used to

reconstruct the original input. However, the generated hash will

always be the same if the same input is utilized. There are

several different kinds of hash functions, including RIPEMD

and SHA (with variations like SHA-0, SHA-1, SHA-2, and

SHA-3), with SHA-256 being frequently employed in

cryptocurrencies like Bitcoin[1] and Bitcoin Cash[154] With an

output size of 256 bits, SHA-256 is very challenging to crack

using brute force techniques. The algorithm also displays the

avalanche effect, where even a small change in the input results

in a very different output [146], as seen in figure 6.

FIGURE 6. Example of SHA-256

Hash functions have three essential characteristics that is

collision-free, hides the input value using the output hash, and

is puzzle-friendly. These characteristics make cryptographic

hash functions trustworthy and secure in a variety of

applications. Hash functions are used in the context of

cryptocurrencies to link blocks of transaction data in the

blockchain, verifying transactions and reducing fraud. By

creating a hash from the header of the previous block, miners

attempt to solve hashes by looking for a hash that matches a set

of requirements. Successful miners are paid and add the block

to the blockchain after a trial-and-error process involving a

nonce. In order to create fixed-length hashes, preserve data

integrity, and secure data within the blockchain, hash functions

are essential. They undergo network participant scrutiny and

data integrity validation. In Bitcoin, the hashes consist of 64

digits [144-146].

A hash function is a mathematical operation that transforms

an input string of any length into an output string with a

predetermined length. We have listed some real world aspects

where hashing plays an important role as:

● Password Verification

Almost all websites store passwords as hashes since it is risky

to store passwords in ordinary text files. The password entered

by the user is hashed, and the hashed value is compared with a

list kept on the company's servers. This is not a foolproof

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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method, though; hackers have produced rainbow tables—

databases of popular passwords and their hashes—that facilitate

their access to accounts whose credentials have been

compromised.

Hagui et.al.,[171] proposed a novel hybrid biometric pattern

which combines password and picture elements for better user

authentication security followed by a secure pattern

communication between the access point and the node database,

blockchain technology and lightweight encryption are also

used. Furthermore, the matching mechanism compares

password and image attributes with database entries to confirm

validity.

● SIGNATURE GENERATION AND VERIFICATION: Digital

documents or messages can be authenticated digitally by

using a mathematical method called signature verification.

Once all requirements are met, a valid digital signature

provides strong evidence to the recipient that the message

was created by a known sender and was not altered during

transit.

The author in [172] implemented an ECDSA dependent

pairing-free based signature aggregation approach which uses

first aggregate signature technique for signature aggregation

and verification in blockchain applications that is

computationally efficient and doesn't require additional

parameters or charges. Furthermore, the creation of group

elements is done using the secure secp256k1 elliptic curve, and

the creation of signatures is done using ECDSA.

● VERIFYING FILE AND MESSAGE INTEGRITY: Hashing

can guarantee that files and messages are not altered while

being sent from one party to another. It creates a "chain of

trust." To ensure alignment, a user may, for instance,

publish a hashed version of their data along with the key,

allowing recipients to compare their computed hash value

to the published value.

The study [173] suggests a reliable approach that makes use of

a cryptographic hash function and the conventional

cryptographic method to create a new hash. The system

presented here uses a genetic algorithm (GA) approach for

optimisation and is backed by a hashing algorithm to enhance

overall data surveillance.

c: CRYPTOGRAPHY

Blockchain technology relies on cryptography to ensure trust

and do away with the need for a central mediator. Hash

functions are used to generate digital signatures and link blocks

in a blockchain, whereas public key cryptography is used for

encryption and digital signatures[147][148] . Zero-knowledge

proofs [42] are also employed to provide users more anonymity.

Blockchain technology develops an immutable, secure, and

reliable distributed ledger by using these cryptographic building

elements like Rivest-Shamir-Adleman encryption (RSA),

Elliptic Curve Cryptography (ECC). ECC is a public-key

encryption technique comparable to RSA that achieves security

through the use of elliptic curves. ECC uses far smaller keys

than RSA and provides a similar level of security, therefore it

does not require large prime numbers. Through the special

characteristics of elliptic curves, this method improves the

security of sensitive data [149] [150]. The benefits of using

cryptography in blockchain include security against hacking

and unauthorized access, as well as anonymity and privacy.

However, implementing and verifying complex algorithms can

be challenging, and cryptography alone cannot solve all

security issues [43].

FIGURE 7. Structure of blockchain[1]

Figure 7. illustrates how the block header stores information

about the block, including a timestamp, the hash of the block

before it, and a unique digital fingerprint generated during

hashing. The Merkle Tree is used to organize and verify a

block's transactions, and the block header includes the Merkle

Root for easy verification. In PoW consensus techniques, the

Nonce is used to verify a block's validity. These elements come

together to create a chain of blocks that gives a blockchain its

security and transparency [1][2].

The development of blockchain technology has accelerated

due to the recent growth of the cryptocurrency industry. As

cryptocurrencies gain popularity, more money is being invested

in blockchain-related projects, which has led to the

development of new tools, services, and applications.

Furthermore, the development of blockchain technology has

been influenced by the progress made in distributed ledger

technology (DLT) [7][8]. Blockchain technology appears to be

a game-changing instrument that could change how we transact

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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business, communicate with one another, and protect our data

in the modern world. Blockchain technology is anticipated to

develop further with ongoing funding and research and play a

significant role in the digital economy.

Dedeoglu et al. [7] offered a layered architecture to improve

trust in IoT applications created on the blockchain. Additional

applications that record physical observations on blockchains

can make use of the described architecture. The data that the

gateways get from nearby sensor nodes, the node's reputation,

and the confidence of the observation are used to calculate the

trust for sensor observations at the data layer. The number of

sensor nodes in a cluster with highly correlated data, K,

determines the computational cost of calculating the trust

values, which is given by the equation O(K2). The suggested

design is transferable to the most popular public and private

blockchain platforms and has been tested for end-to-end

performance on a dedicated private blockchain.

Liu et al. [8] demonstrates the significance of governance

for ensuring the smooth operation and ongoing development of

blockchain networks. However, the majority of previous

research just offers general recommendations without

considering building design into account. The authors suggest

a reference architecture to assist architects in designing and

creating blockchain systems that are driven by governance

while operationalizing governance techniques. They apply a set

of architectural patterns for governance to the elements of a

well-known blockchain reference model, outlining the duties of

each element. By mapping it to two current blockchain system

designs, the suggested reference architecture's accuracy and

usefulness are assessed. The authors intend to create decision

models for blockchain system architecture that is driven by

governance in later works.

5) HARDWARE LAYER AND WORKING OF BLOCKCHAIN

a: HARDWARE LAYER

In a blockchain architecture, nodes, mining apparatus, network

infrastructure, storage devices, security protocols, and

scalability solutions make up the hardware layer. Nodes take

part in consensus-building, validate transactions, and interact

with the network. Mining equipment solves complex problems

for PoW blockchains. Network infrastructure ensures

communication and data synchronization. Storage devices store

blockchain data, and security measures protect the network.

Scalability solutions address network growth [44].

b: WORKING OF BLOCKCHAIN

The actions depicted in Figure 8. are part of a blockchain

transaction. A transaction is generated, encrypted, added to a

block, validated by other network users, added to the chain as a

new block, and stored on several computers. The amount to be

transferred, the input transactions, and the recipient's public key

hash determine how a Bitcoin transaction is constructed and

confirmed. Digital signatures are created by encrypting the

transaction identity, which is used to identify transactions,

using the sender's private key. The recipient confirms that the

signature is authentic and that the transaction outputs from the

relevant input transaction are unused before approving the

transaction.

FIGURE 8. Working of blockchain [45].

Another crucial factor in determining the legitimacy of a

transaction is conservation of value. Every transaction has a

redeemable output that the recipient can claim ownership of

with the aid of a private key and a public key hash. Bitcoin

consensus is established through the use of proof of work,

which involves resolving a cryptographic problem in order to

authenticate the addition of a block to the shared ledger.

Verifying the transactions, the hash of the previous block, the

precision of the timestamp, and the proof of work for the most

recent block are all necessary for block validation [45] [46].

B. TYPES OF BLOCKCHAIN

The types of blockchain can be categorized based on their

accessibility and control. Public blockchains are decentralized

and accessible to anyone, private blockchains are controlled and

accessible by specific individuals or organizations, and

consortium blockchains are controlled by a group of

organizations while still maintaining some of the benefits of

decentralization and hybrid contains properties of both private

and public. The categorization helps to distinguish the

characteristics and use cases of different blockchain types.

FIGURE 9. Types of blockchain[155].

There are four different kinds of blockchains—public, private,

consortium and hybrid as shown in figure 9.

a: PUBLIC BLOCKCHAIN

Public blockchains are open to all users and have no access

restrictions, making it possible for anybody to join and take part

in the network. They are mostly utilized for cryptocurrency

exchange and sustain confidence by rewarding users that add to

the network. Public blockchains include those used by Bitcoin,

Litecoin, and Ethereum. Public blockchains feature high levels

of security and transparency, but they are difficult to scale, have

sluggish transaction times, and use a lot of energy [11] [12].

b: PRIVATE BLOCKCHAIN

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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Blockchains that operate in closed networks and are

permissioned and constrained are known as private

blockchains. It is frequently used in groups when participation

is restricted to a select few people. Private blockchains offer

better transaction per second (TPS) and scalability than public

blockchains but are less decentralized and secure. Private

blockchains' controlled network structure makes it challenging

to build trust in them. The private blockchains Hyperledger

Fabric [70], and Hyperledger Sawtooth [71], Corda [23] are

among examples. Anyone can sign up for the Blockchain

Council and become Certified Blockchain Experts to learn

about blockchain technology in practice [47] [48].

c: CONSORTIUM BLOCKCHAIN

Consortium blockchain refers to a permissioned, semi-private

blockchain. Consortium blockchains, in contrast to private and

public blockchains, are partially centralized because they give

control over the block validation process to a predetermined

number of nodes via the use of multiple signatures. However, if

a majority gains control, the consortium's power could result in

blockchain tampering, and read or write access might only be

granted to network users. Although the agreement is not limited

to a certain group of nodes, immutability and irreversibility are

not assured. The Energy Web Foundation and the IBM Food

Trust are two instances of consortium blockchains. Compared

to other blockchains, it is less transparent and anonymous even

if it offers security and scalability [46].

d: HYBRID BLOCKCHAIN

In [49] states that centralized systems face issues with

connectivity and security, leading to potential system failures.

Decentralized systems, such as Blockchain, have emerged as an

alternative solution. However, scalability and reliability

problems have arisen with the popularity of cryptocurrencies

like Bitcoin[1]. To address these issues, a hybrid Blockchain

architecture is proposed, suitable for banks and e-commerce

businesses. It allows users to connect using personal

Blockchains, while servers share a chain of Blockchains within

the private network. Miners governed by business policies

control block appending and hash mapping, reducing power

consumption and improving system security. The hybrid

solution combines the benefits of both centralized and

decentralized systems, offering resource sharing, scalability,

and fault-tolerance.

C. CHARACTERISTICS OF BLOCKCHAIN

Blockchain technology offers a decentralized, transparent, and

safe ledger system for recording transactions[2]. It is a useful

tool for supply chain management and finance since it offers an

unchangeable record of transactions that cannot be altered

without network consent. Table 2 shows the variety of

technologies that are utilized to support each feature.

TABLE 2. Characteristics table of Blockchain

Characteristics

Description

Technology Behind

Immutable

A record that has been added to a blockchain is said to be immutable, meaning that it

cannot be changed after that. With a permanent and impenetrable record of transactions,

this feature makes blockchain technology extremely dependable and safe.

Distributed ledger technology

(DLT)and Cryptography

Distributed

Distributed property in blockchain allows individuals to own and control digital assets

without a central authority. It provides secure and immutable transaction records shared

among multiple parties, with a consensus mechanism for agreement on the current state

of the ledger and transaction validity.

Distributed ledger technology

(DLT)

Decentralized

Decentralized property in blockchain is the storage and protection of digital assets on a

distributed ledger system, managed by a decentralized network of computers. The

consensus protocol ensures agreement among participants on asset status and maintains

a secure and accurate record of transactions, making it a trustworthy system for digital

asset management.

Consensus protocol

Security

Blockchain technology enables secure and immutable storage, management, and transfer

of digital assets using a distributed ledger system. Its security is based on cryptography

and distributed consensus algorithms, ensuring data protection and agreement among all

network nodes on the blockchain state.

Cryptography, Consensus

algorithms

Trust

Blockchain technology offers trust through its immutable ledger, which is verified and

secured by network consensus, making data tampering almost impossible. Smart

contracts also enhance trust by enabling automated contracts that ensure accountability

and compliance with contract terms by all parties involved

Cryptography, Consensus

algorithms, smart contracts

Privacy

Blockchain's privacy feature is enabled by cryptographic hashing and zero-knowledge

proofs, which securely store data on the blockchain while keeping it anonymous and

allow users to prove possession of information without revealing it. This is essential for

sensitive applications like healthcare and finance, giving users confidence that their data

is both private and secure

Cryptographic hashing or zero-

knowledge proofs

D. APPLICATION OF BLOCKCHAIN IN IOT ENABLED

ENVIRONMENT

As shown in Figure 10. Education, Healthcare, Finance, Supply

chain and E-Governance are just a few of the many uses for

blockchain technology. Its decentralized, secure, and

transparent nature makes it a valuable tool for creating trust and

improving efficiency in various industries.

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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FIGURE 10. Applications of blockchain in IoT [68].

1) EDUCATION

Li et al. [50] describes a study that examined the education

credentialing environment with the potential of blockchain. The

study assessed the selected initiatives using a four-layer

architecture and came to some recommendations that may direct

the future work of researchers and practitioners of blockchain in

education. But the study had drawbacks because it was designed

with a small sample size and, because of space limitations, it

was unable to provide a novel alternative. The following steps

in the project include increasing user acceptance and

involvement through a co-design strategy and creating a

blockchain prototype that is extensible and pluggable while

considering technical challenges and working with other

blockchain solutions.

Ocheja et al. [51] carried out a bibliometric and qualitative

analysis of blockchain research in education. The field's current

situation was shown by the bibliometric study, which also

revealed trends in co-occurrences, author contributions,

publication growth, and topic progression. The investigation

reflected that there are not enough partnerships and a dedicated

community for blockchain education research. Few publications

provided useful solutions or had any connection to the primary

educational framework, according to a qualitative study

conducted with content analysis. Furthermore, the use of

blockchain for academic credentials attracted greater interest

than other use cases. As examples of how blockchain might

meet demands linked to education beyond diplomas, two case

studies were presented: the Blockchain of Learning Logs

(BOLL) and the Smart Ecosystem for Learning and Inclusion

(SELI) initiatives. As ground-breaking ideas, the potential

advantages of employing blockchain technology for academic

record transfer, learning data traceability, inclusiveness,

privacy, and information security were emphasized. In

overcoming the issues related with blockchain technology's

scalability, processing speed, and data capacity, it is clear that

its implementation in the field of education could see significant

growth in the future. Mohammad et al. [52] review highlights

the blockchain technology's promising application in higher

education and lists the difficulties in implementing it. Based on

the Technology Organization Environment (TOE) framework,

the study categorized the problems into three groups:

technological, organizational, and environmental. In

comparison to organizational and environmental problems

including financial constraints and legal concerns, technological

challenges such poor usability, scalability, and standardization

garnered more emphasis in the evaluated studies. In order to

boost the use of blockchain technology in education, the

analysis highlights a research gap regarding the latter issues and

recommends conducting additional organizational and

environmental research. In order to solve the research issue, a

literature review was conducted, and the review provides

information on the topics that have attracted increased scholarly

attention.

2) HEALTHCARE

Agbo et al. [53] proposed a systematic review identified use

cases, sample applications, challenges, existing methodology,

and possibilities for additional research in order to understand

the state of the art of blockchain technology in the healthcare

industry. The review examined 65 papers to provide answers to

the study's aims. Blockchain was discovered to have a number

of applications in the healthcare industry, including the

management of the supply chain, the archiving of electronic

medical records, the conduct of biomedical research, patient

monitoring, and health data analysis. More research is still

required to ascertain the advantages of blockchain technology

in the healthcare sector and to address issues like scalability,

interoperability, security, and privacy, despite the development

of a few blockchain-based healthcare apps. The article claims

that blockchain technology has developed into a multipurpose

instrument with uses in the healthcare industry.

Ramzan et al. [54] addressed how important blockchain

technology is to many different sectors, including healthcare.

With the use of this technology, it is possible to have

transparency, security, and great quality for less money.

Describe the current state of blockchain research, healthcare use

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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cases, challenges, and future directions in this article. Three

categories of research—Supply Chain Management (SCM),

IoT, and healthcare management—have been established based

on blockchain applications in the medical field. Important

healthcare projects, motivations, applications, use cases, plus

strengths, weaknesses, and challenges are all discussed in the

article. SCM, electronic medical records, remote patient

monitoring, and the analysis of health data are just a few of the

covered use cases for blockchain applications in the healthcare

sector.

Attaran et al. [55] proposed use of blockchain technology in

healthcare is still being researched, but an examination of the

literature shows that the number of suggested solutions is

growing quickly. Blockchain is promoted as a game-changing

technology that can decrease costs while enhancing access

control, interoperability, provenance, and data integrity in the

healthcare industry. In this article, many blockchain

applications and use cases in healthcare are examined, including

patient engagement, genetic research, and the management of

the supply chain for medications. Blockchain technology needs

to be improved further before it can be used in the healthcare

industry. Legal and regulatory difficulties must be resolved. The

article comes to the conclusion that while blockchain in

healthcare is still in its early stages, it has a lot of potential going

forward and that additional study into practical applications is

required.

Vyas et al. [56] proposed the use of electronic storage of

medical records, including prescriptions, has become common

among healthcare providers, patients, and other stakeholders.

But for data and identity protection, this private patient data

needs to be stored decentralized. A single patient medical

history report that presents only the most important data and is

safely maintained on a decentralized blockchain network for

later use can be made using blockchain-based architectures in

conjunction with AI methods like optical character recognition

(OCR). The paradigm-shifting nature of this approach to

healthcare administration is suggested, and the value of machine

learning models in healthcare has been proved by numerous

research. The use of AI to select and prioritize certain patients

for dose tracking in order to reduce turnaround times is one of

the predicted future developments. This is an exciting area for

study and innovation since governments and key corporate

sectors are getting more involved in digitizing healthcare

systems globally.

3) FINANCE

Pombo-Romero et al. [57] discussed the possibility for

developing financial instruments for photovoltaic irrigation

(PVI) projects, which can aid in sustainability by lowering water

use and greenhouse gas emissions. By using decentralized

finance (DeFi) solutions, financial instruments may be more

affordable and effective, which may draw more long-term

funding for PVI projects. The ensuing cost decrease can make

PVI more competitive with alternatives based on fossil fuels,

hastening the shift to a sustainable energy strategy for irrigated

agriculture. The use of smart contracts and tokenized currency

flows is not without risk, though, and these risks must be

addressed through further research and pilot projects. The

proposed methodology is also applicable to other green asset

classes, and it may be made even more valuable by combining

green certificates and power purchase agreements (PPAs) into a

single smart contract.

Younus et al. [58] highlighted the need for improved standards

across the board in banking and financial services as well as the

possibility for decentralized solutions offered by blockchain

technology to maintain the secrecy and integrity of financial

data. The paper explores the idea of smart contracts for

blockchain-based financial systems and discusses the needs and

difficulties for such systems. In the financial and banking

industries, it also identifies major application areas where

blockchain technology may be a helpful addition.

Kucukaltan et al. [59] highlighted that to utilize blockchain's

promise in e-governance, policymakers must have a solid

understanding of the technology. Eliminating third-party

intermediaries through the use of blockchain in smart cities will

increase transparency and trust. New business models in supply

chain and energy trading will emerge as a result of blockchain

integration with smart cities, which will be advantageous to both

private people and public institutions. The use of technologies

like blockchain, IoT, and AI will lead to a huge increase in

citizen participation in decision-making processes. The study

also demonstrates that different goals are pursued in

industrialized and poor nations when implementing blockchain

technology. The research helps both developed and developing

nations create environments that are effective and efficient for

supply chains. In order to identify new themes and patterns, the

study used web analytics to examine Google searches and

queries related to blockchain, supply chains, and financial

interactions.

Shahbazi et al. [60] examined the application of the

Reinforcement Learning (RL) technology and the Hierarchical

Risk Parity (HRP) asset allocation approach for bitcoin network

risk management. Results from high-performance assessments

were obtained using RL in contrast to other machine learning

methods. HRP improved risk management and added desired

diversification to the process. The suggested method will be

enhanced by adding out-of-sample testing performance in more

assets and classes and by using optimisation techniques for

better risk management performance.

4) SUPPLY CHAIN

Chang et al. [61] provided a comprehensive analysis of the

research on blockchain technology (BCT) potential uses and

difficulties in supply chain management. Due to its key

advantages, such as accountability, efficiency, traceability,

transparency, dependability, and security, BCT has been widely

utilized in SCM. Confidentiality, immutability, and scalability

continue to be major obstacles. Despite significant attempts to

investigate BCT's potential in numerous domains, including

SCM, some BCT traits are absent or scarce. The business,

management, and accounting areas have produced the greatest

number of publications on SCM and BCT. Additionally, there

are strong connections between BCT and the IoT, which is

congruent with the upcoming Blockchain and IoT (BIoT) age.

Kaur et al. [62] provided a succinct review of the literature

encompassing sixty research papers on the use of IoT and

blockchain in food supply chain management (FSCM). By

examining the possible uses and limitations of blockchain

technology in the FSCM, researchers can forecast future

opportunities for developing Internet of Things applications.

The study found that smart contracts and blockchain technology

may increase FSC trading activity and enhance food traceability

by promoting cooperative relationships and improving

operational efficiencies. The blockchain technology in the food

supply chain is explored in this paper as a roadmap for future

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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research issues. Both the technological adoption of blockchain

and the adoption of problems for the food chain with IoT

devices are covered in this article.

5) E-GOVERNANCE

Khanna et al. [63] discussed the expanding range of uses for

blockchain outside the banking industry because of its benefits

including immutability, data traceability, and security. A

literature study is conducted to identify important areas where

blockchain can have a positive impact on smart city governance,

the authors investigate how blockchain might be utilized to

enable smart cities. The results indicate that blockchain can be

used in sustainable smart cities along with other disruptive

technologies like IoT and AI. To benefit from blockchain's

promise in e-governance, policymakers must comprehend it. By

eliminating third-party intermediaries, the integration of

blockchain with smart cities will increase transparency and

trust. The integration of blockchain with smart cities will lead

to the emergence of new supply chain and energy trading

business models that will benefit both private citizens and

governmental institutions. Decision-making procedures for

public engagement will noticeably speed up with the usage of

technologies like blockchain, IoT, and AI.

Kaur et al. [64] examined the benefits and challenges of

employing blockchain technology to automate e-government

processes. Through the research of four case studies, the essay

explores how blockchain could help e-government reforms and

expedite public information management procedures. The

distributed ledger system can be used to securely and

transparently disseminate information about registered

processes and procedures among numerous stakeholders in

order to improve openness and accountability in governmental

operations. However, difficulties with regulatory conflicts and

data leaks must also be dealt with when automating e-

government procedures. Overall, by making e-government

more effective, accountable, and transparent, blockchain

technology has the ability to radically transform public service

delivery paradigms.

Lo et al. [65] discussed the potential advantages of a

transnational digital single market in Europe, with a view to

expanding accessibility to data and fostering viability. By

reducing bureaucratic procedures and fostering citizen trust, the

GLASS project aims to create a data-sharing model that is

focused on the citizen. To encrypt and store verified credentials,

the authors suggest combining Hyperledger Fabric with IPFS.

This will guarantee that only trustworthy users with the

appropriate rights can access blockchain records and encryption

keys. To test scalability and performance, the authors want to

deploy each component on a different system while also

evaluating encryption operations and integrating key

components with a user wallet.

Wahab et al. [66] discussed the significance of elections as a

key democratic instrument and the rising use of computerized

voting machines in many nations. Due to Ethereum's

consistency, widespread adoption, and availability of smart

contract logic, the study provides a safe blockchain-based

framework for electronic voting in Iraq. This framework makes

use of Ethereum's network. This architecture provides a

transparent election process with accurate vote counting while

ensuring security, voter convenience, cost savings, increased

authentication, and eliminating duplicate voting. An increase in

voter turnout is anticipated as a result of the deployment of this

system.

Goldsmith et al. [67] proposed a study on the possible

application of blockchain technology to Oman's governance

issues. To improve the efficacy, economy, and legitimacy of

public administration and governance tasks, the study highlights

seven key governance concerns and considers the possibilities

of blockchain solutions. However, to calculate the cost/benefit

ratio of blockchain solutions in each governance area, focused

quantitative studies are required. The need for additional

research in the areas of tax and employment reform has been

identified. The study comes to the conclusion that, despite the

fact that Oman should immediately implement blockchain

solutions, there may be political opposition to the government's

decision to switch from a centralized system of trust to a

decentralized method of building trust based on technology.

Sunny et al. [68] discussed the benefits and drawbacks of

implementing blockchain technology across a range of sectors,

including the IoT, supply chain, banking, education, and

healthcare. The most recent research articles were examined by

the authors in order to analyze the possible effects of blockchain

across various industries. They discovered that while

blockchain technology benefits businesses, it also has certain

limitations, like a lengthy confirmation process for transactions

and expensive installation costs. Before implementing a new

technology, the authors advise stakeholders to ascertain their

needs and the benefits and disadvantages of the technology.

They also highlight new government initiatives and industrial

IoT applications for many industries, and they recommend that

future studies consider any particular difficulties that

blockchain may present in the development of smart cities and

transportation systems. Even though the study has some

methodological flaws, academics can still utilize it to look at

blockchain's potential future applications.

E. BLOCKCHAIN PLATFORMS

Blockchain platforms are software infrastructures that provide

the necessary tools and resources for developing, deploying, and

running decentralized applications on a blockchain network.

They enable developers to build and deploy smart contracts,

manage digital assets, and perform other functions related to

blockchain development. Ethereum [22], Hyperledger Fabric

[70] and Corda [23] are a few well-known blockchain platforms.

These platforms offer features such as smart contract

functionality, distributed ledger technology, consensus

algorithms, scalability solutions, privacy and security, and

more. Developers choose a platform based on their specific

needs and requirements for their decentralized application. As

shown in Table 3. a comparison of different types of blockchain

platforms, including their pros and cons.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

TABLE 3. Comparison of different types of blockchain platform

Platfo

Consensu

Protocol

Network

Permissio

Trans

action

s per

Secon

Block

Confirma

tion Time

Transa

ction

Cost

Coin

Description

Important

Features

Limitatio

Year

Ref

ere

nces

Bitcoin

Proof of

Work

(PoW)

Permission

less

minutes

Variabl

BTC

The first

decentralized

cryptocurrency

and blockchain

platform.

Decentralization,

Security, Scarcity,

Global Adoption

Scalability

, Energy

Consumpt

ion

2009

[1]

Ethere

Proof of

Stake

(PoS)

Permission

less

15-30k

10-20

seconds

Variabl

ETH

A decentralized

platform for

executing smart

contracts and

building

decentralized

applications.

Smart Contracts,

Decentralized

Finance (DeFi),

Ethereum Virtual

Machine (EVM)

Scalability

, Gas

Fees,

Environm

ental

Impact

2015

[22]

IBM

Blockc

hain

Varies

Varie

A blockchain

solution provided

by IBM for

enterprise-level

use cases.

Enterprise

Integration,

Privacy, Security,

Hyperledger

Framework

Platform-

specific,

Limited

Public

Blockchai

Adoption

2016

[69]

Hyperl

edger

Fabric

Varies

(e.g.,

PoW,

PoS)

Permission

Varies

Varie

A blockchain

platform for

businesses that is

open source and

created by the

Linux

Foundation.

Modular

Architecture,

Scalability,

Privacy,

Permissioned

Consensus

Complexit

y for Non-

Technical

Users,

Learning

Curve

2015

[70]

Hyperl

edger

Sawto

oth

PoET

(Proof of

Elapsed

Time)

Permission

Varies

Varie

The Linux

Foundation built

an open-source

enterprise

blockchain

platform.

Scalability,

Consensus

Pluggability,

Transaction

Families,

Ethereum

Compatibility

Less

Mature,

Limited

Document

ation and

Communit

y Support

2015

[71]

Ripple

Protocol

Consensu

Algorithm

(RPCA)

Permission

1,500

3-5

seconds

Low

XRP

A network for

remittances,

currency

exchange, and

real-time gross

settlement.

Fast and Low-Cost

Transactions,

Banking

Partnerships,

Liquidity Provider

Centraliza

tion

Concerns,

Pre-Mined

Distributio

n Model

2012

[72]

[30]

Stellar

Consensu

s Protocol

(SCP)

Permission

less

1,000-

10,000

3-5

seconds

Low

XLM

A decentralized

platform for

cross-border

transactions and

issuing digital

assets.

Fast and Low-Cost

Transactions,

Stellar

Decentralized

Exchange,

Anchors

Limited

Adoption,

Ecosystem

Compared

Ethereum

2014

[31]

EOSIO

Delegated

Proof of

Stake

(DPoS)

Permission

4,000

Sub-

second

Low

EOS

A blockchain

platform for

building

decentralized

applications with

high scalability.

Fast Transaction

Speed, Parallel

Processing,

Governance Model

through Elected

Block Producers

Critics

Argue

Less

Decentrali

zation due

to Elected

Block

Producers,

Governan

Concerns

2017

[73]

Corda

Notary-

based

Permission

Varies

Varie

A blockchain

platform that is

open-source and

made for the

financial sector.

Privacy,

Interoperability,

Smart Contract

Compatibility

Limited

Use Cases

Outside

Financial

Industry,

Relatively

Less

Mature

2016

[23]

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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Hedera

Hashgr

aph

Hashgrap

Consensu

Algorithm

Permission

10,000

Seconds

Low

HBA

A distributed

ledger

technology

platform with

high throughput

and low fees.

High Transaction

Speed,

Asynchronous

Byzantine Fault

Tolerance (aBFT)

Consensus

Relatively

New,

Governan

ce Model

with

Trusted

Nodes,

Centraliza

tion

Concerns

2018

[74]

NEO

Delegated

Byzantine

Fault

Tolerance

(dBFT)

Permission

1,000

15-20

seconds

Low

NEO

A blockchain

platform for

digitizing assets

and building

smart contracts.

High Transaction

Speed, Multiple

Programming

Language Support

Centralize

Governan

ce during

Initial

Stages,

Transition

ing to

Decentrali

zation

Model

2014

[34]

Tron

Delegated

Proof of

Stake

(DPoS)

Permission

less

2,000

seconds

Low

TRX

A decentralized

platform for

content sharing

and

entertainment

applications.

High Transaction

Speed, Focus on

the Entertainment

Industry

Plagiarism

Controver

sies,

Centraliza

tion

Concerns

2017

[75]

Multic

hain

Custom

Permission

Varies

Varie

A platform for

building private

blockchain

networks for

specific use

cases.

Customizable

Permissions and

Consensus

Mechanisms,

Private Blockchain

Capabilities

Limited

Scalability

Compared

to Some

Other

Platforms,

Primarily

for Private

Use Cases

2012

[76]

Binanc

Tendermi

Byzantine

Fault

Tolerance

(BFT)

Permission

10,000

1-2

seconds

Low

BNB

A blockchain

platform

launched by the

Binance

cryptocurrency

exchange.

High Transaction

Speed,

Compatibility with

Binance

Ecosystem

Limited

Adoption

Outside

Binance

Ecosystem

Relatively

New

Platform

2017

[77]

The correct blockchain platform must be selected for a project's

unique needs, taking into account aspects like privacy,

decentralization, scalability, security, and cost. Public

blockchains are well suited for decentralized applications that

need openness and trust, whereas private blockchains are better

suited for applications that need more discretion and privacy

[70]. With a balance between privacy, control, and

decentralization, hybrid and consortium blockchains offer a

middle ground between the two.

III. STATISTICAL ANALYSIS

In this review paper, a bibliographic analysis is performed to

investigate the current state of research on the IoT and

blockchain. We used Scopus [156] and Web of Science [157],

two renowned academic databases, to gather pertinent

publications based on the keywords "blockchain" and "IoT." A

total of 47,766 papers with the term "blockchain" were found in

the Scopus database, according to the analysis. The

combination of "blockchain and IoT" was the subject of 8,091

of these papers. On the other hand, 3,372 publications with the

keywords "blockchain and IoT" were located in the Web of

Science database.

Figure 11. shows the Scopus publishing distribution of

blockchain articles by year, which we generated to provide

deeper insight into the temporal trends of publications

connected to the blockchain. A summary of Scopus

publications especially concentrating on the intersection of

blockchain and IoT is shown in Figure 12.

FIGURE 11. Blockchain keyword based publications

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Additionally, Figure 13. shows the subject area distributions of

publications relating to blockchain and IoT, which may be used

to comprehend the wide range of research areas in this field.

The most significant interdisciplinary research domains are

identified by this image.

FIGURE 12. “Blockchain and IoT” keyword publications

FIGURE 13.”Blockchain and IoT” keyword publications

subject area

We also examined the correlation between the years of

publication and citations for works on blockchain and IoT in

Web of Science. Figure 14. presents the results. This graph

shows the evolution of the number of citations, which sheds

light on the importance and impact of research in this area.

We aim to provide scholars with useful information on the

current state of blockchain and IoT research by performing this

analysis.

FIGURE 14. Web of science blockchain and IoT publications

The growth across sub-areas such as supply chain, consensus

algorithms, and healthcare is visualized in the Figure. 15. which

improves the statistical analysis of research paper trends. This

division offers a nuanced perspective that makes it possible to

investigate particular research trends in the context of the larger

field with concentration.

FIGURE 15. Number of Publications in combination with

Blockchain (Web Of Science Database).

IV. BLOCKCHAIN IN IOT BASED ENVIRONMENT

Blockchain technology is used in IoT contexts to enable secure

data interchange, decentralized decision-making, and tamper-

proof record-keeping by interacting with IoT devices [82]. It

offers advantages including greater security, data integrity, and

privacy, as well as increased trust and transparency in IoT

transactions and interactions, which supports effective and

dependable IoT deployments.

Mohanta et al. [78] discussed the issues with privacy and

security that IoT apps face because of their constrained

processing and storage capabilities. For Internet of Things (IoT)

applications, detailed explanations of multiple attack models—

including node capture, replay, side channel, eavesdropping,

false data injection, MITM, DoS, unauthorized access,

spoofing, phishing, sinkhole, and trust management issues—are

given on a layer-by-layer basis. The article also looks at

different security solutions that make use of fog computing,

blockchain technology, and machine intelligence to address

these issues. It also describes how Elliptic Curve Cryptography

(ECC)-based techniques and other lightweight security

protocols are required due to the resource constraints of Internet

of Things devices. The paper emphasizes that every tier of the

IoT infrastructure needs to address security concerns in order to

create a secure network.

Liang et al. [79] proposed a thorough analysis of security

breaches on IoT devices that covers breaches at the physical,

network, and application layers. The authors also go over other

IoT defenses that can be applied, like edge computing,

blockchain, and machine intelligence. The survey seeks to offer

a thorough overview of the available solutions and potential

future research areas for enhancing IoT security. This survey

can assist academics and practitioners in the IoT security area

create better security strategies to safeguard IoT devices and

networks by identifying various threat types and addressing

viable remedies.

IoT is a paradigm that enables embedded sensors to produce,

share, and ingest data with minimal human interference. This

model is made possible by critical developments in

computational power, hardware miniaturization, and network

interconnections. While IoT technologies offer significant

benefits, they also pose new security threats due to their

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

interconnected design and various technological limitations.

Poor design practices, inadequate software upgrades, and

accessible ports create vulnerabilities that attackers can exploit

to reprogram devices and trigger failure. Additionally, the lack

of IoT access control protocols can gi ve attackers the ability to

create malicious IoT-specific behaviors. In order to give insight

on future research paths and technological details for IoT

security, this survey evaluates the body of literature on IoT

vulnerabilities. The absence of Internet-scale solutions to the

issue of IoT stability is one of the biggest obstacles to IoT

resilience. In order to provide effective remedial options,

research efforts must concentrate on identifying IoT assaults

and associated vulnerable behavior. The development of

appropriate systems that address IoT-specific risks must be

incorporated into firmware production cycles to enhance IoT

system protection. Future initiatives may include investigating

various strategies for inferring malicious IoT devices,

observational literature to classify network loads, and

systematic methodologies for producing informative deduction

[80].

Chen et al. [81] proposed a survey of recent research on IoT

assaults and associated defenses, with an emphasis on machine

learning (ML)-based techniques for mitigate attacks on IoT

networks. A review of IIoT security, specifically as it relates to

Industrial Control Systems, comes after the introduction of IoT

and Industrial IoT (IIoT). The article presents common attacks

and Advanced Persistent Threat (APT) attacks in an IoT

network, along with an attack taxonomy and the distribution of

APT assaults inside it. To display attack vectors and

vulnerabilities in IIoT networks, the Process for Attack

Simulation and Threat Analysis (PASTA) threat model is used.

The article enumerates three types of network intrusion

detection strategies: hybrid, anomaly-based, and signature-

based. The paper focuses on anomaly-based and hybrid

approaches to detect and classify attacks on IoT networks, and

it proposes ML-based methods as a feasible way to improve

detection performance and reduce attacks. The essay also

compares and evaluates ML algorithms based on how well they

can recognise different kinds of attacks. The paper ends by

outlining open issues and challenges for network infiltration

based on ML approaches as well as those for protecting IoT

networks from APT assaults, in order to benefit researchers

working in IoT, IIoT, ML, and cybersecurity.

Panarello et al. [82] explore the adoption of blockchain

technology to address security, privacy, and data integrity

concerns within the IoT ecosystem. The essay analyzes two

usage patterns—device manipulation and data management—

and draws attention to how far along some of the proposed

solutions are in their development. The authors suggest that

future research should focus on developing solutions for data

privacy and integrity and designing systems to manage device

identity in a tamper-proof manner. While research in this

direction is in an early phase, the article highlights the potential

of blockchain to streamline negotiation processes and eliminate

the need for a trusted intermediary, making it an interesting

solution for data exchange and trading in the machine economy.

Huo et al. [83] referred to a thorough analysis of how

blockchain technology is used in the IIoT. The authors review

the body of knowledge on IIoT and underline the advantages of

using blockchain in this field. They also talk about platform

implementation examples and the difficulties in developing the

IIoT. The study also makes recommendations for how to

address these issues and advocates combining blockchain and

other cutting-edge technologies with IIoT to better support the

manufacturing process. The goal of the paper is to serve as a

resource for blockchain researchers to comprehend the existing

state of affairs and difficulties facing blockchain in IIoT, as well

as to recommend future research possibilities. The authors

stress that there are still many obstacles in the way of using

blockchain technology in IIoT, and that overcoming these

obstacles will be a key area of focus for future study.

Samaniego et al. [84] discussed IoT systems that may create,

store, and transfer digital assets in a secure and tamper-proof

manner by leveraging blockchain technology. The hosting

environment for Blockchain as a Service (BaaS) for IoT is a

significant obstacle, nevertheless. Potential hosts include

clouds or fog computing, although edge devices sometimes

have insufficient computational power and bandwidth. The

performance-affecting element identified by the article that

assesses the utilization of fog and cloud computing as hosting

platforms is network latency. As a result, when it comes to

hosting BaaS for IoT systems, fog trumps cloud.

During IoT working, blockchain can be used in several areas

to enhance security, trust, and efficiency as shown in Figure 16.

FIGURE 16. Blockchain scope in IoT

A. DEVICE IDENTITY AND SECURITY

1) DEVICE IDENTITY AND AUTHENTICATION

For device identification verification and authentication,

blockchain technology may provide a decentralized,

impermeable system. It enables secure and unique

identification of IoT devices, ensuring that only authorized

devices can interact with the network.

Bouras et al. [85] introduced an approach that is simple for

managing IDs in the IoT using a consortium blockchain. It

discusses identity management's design, architecture, and many

functions as well as the advantages of using a permissioned

blockchain for scalability and security. Identity lookup for IoT

sensors, automatic registration, and multi-factor authentication

will be the main topics of future research.

Das et al. [86] proposed a secure framework for managing

vehicle identities on the blockchain in intelligent transportation

systems. It emphasizes the importance of data security, privacy,

and the need to educate users about safeguarding their private

keys. The performance of the identity generation process will

be improved, and zero-knowledge proof-based encryption

approaches will be investigated.

Venkatraman et al. [87] presented a proof-of-concept

model for creating an IoT identity management system based

on blockchain. Data modeling and personalized smart contracts

are used to show the system's applicability in real-world

situations. Future research will examine the scalability,

flexibility, and performance indicators in actual commercial

settings.

Rashid et al. [88] introduced a blockchain-based IoT

authentication method that permits safe cross-communication.

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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The suggested plan guarantees non-repudiation and data

integrity. It has been evaluated on the open Ethereum

blockchain network and exhibits high effectiveness and cheap

cost. Future ideas include testing on certain devices like the

Raspberry PI and refining the implementation technique.

2) DATA INTEGRITY AND SECURITY

Blockchain technology offers an unchangeable and transparent

ledger, which helps to guarantee the security and integrity of

IoT data. On the blockchain, data from IoT devices may be

safely validated and stored, avoiding manipulation or unwanted

access.

Maftei et al. [89] proposed a blockchain-based method for

organizing and storing massive amounts of data from Internet

of Things devices in wireless sensor networks. To ensure safe

data management, the design leverages the immutability,

decentralization, and consensus process of blockchain

technology. In order to scale over many wireless

communication protocols and communicate preset information,

it uses a lightweight blockchain and smart contracts. The

suggested design provides low latency and fast throughput,

enabling for the performance-preserving integration of several

IoT devices. Future work will examine application-specific

approaches and evaluate the architecture in actual operational

environments.

Li et al. [90] presents a secure scheme for storing and

protecting IoT data using blockchain. The scheme incorporates

edge computing and certificateless cryptography for data

storage management and authentication. By leveraging

blockchain, the scheme offers a platform for broadcasting

public keys and achieves authentication and accountability. The

combination of blockchain, certificateless cryptography, and

edge computing enabling extensive IoT data storage is

presented in this study for the first time. The authentication

mechanism has to be improved, and future work should look

into comprehensive designs for sophisticated access control

policies.

Huh et al. [91], proposed A method for using the Ethereum

blockchain to manage Internet of Things devices. By storing

data from meters and telephones, smart contracts enable

continuous gadget upgrading and control. Future research aims

to construct a fully-scaled IoT system with numerous devices.

The proof of concept shows the system's viability. By offering

quick and effective service while tackling synchronization and

denial of service assaults, the experiment seeks to enhance IoT.

Hannah et al. [92] proposed a blockchain-based deep neural

network (DNN) to optimize data transport from IoT sensing

nodes to the target in response to user requests. The

recommended solution is put into practise in a healthcare

administration system to enable faster data transfer. Real-time

data testing demonstrates that health monitoring and

classification offer the best accuracy and fastest possible

response times for user inquiries. The results of the simulation

show that, in comparison to current blockchain data transfer

methods, the proposed technique answers the query promptly

and precisely. In the future, machine learning or deep learning

optimization can be used to improve blockchain modeling in a

distributed ledger, resulting in efficient address ledgering.

Azbeg et al. [93] provides a review of IoT and blockchain

applications in the healthcare sector. It talks about how

wearables and IoT devices are proliferating and how they may

gather, analyze, and exchange health data with medical

professionals. As a secure method of storing and transmitting

sensitive healthcare data, blockchain technology is introduced.

The article discusses a number of current uses, including remote

patient monitoring, disease forecasting, and medicine tracing.

Future research topics are also highlighted, along with the

difficulties and potential solutions for incorporating blockchain

in healthcare IoT systems. For additional research, the

document acts as a condensed state-of-the-art review.

There will likely be more security issues as the IoT combines

with other technologies like big data, cloud computing, and

artificial intelligence (AI). As both technologies encourage

decentralization, integration of IoT with blockchain will boost

the dependability and stability of data and systems. Blockchain

provides reliable information exchange, safe data storage, and

trustworthy node authentication. It may also offer access

authentication and data protection for IoT devices, as well as

ensuring the protection of privacy and anonymity and reducing

single points of failure. The use of blockchain in the IoT will be

problematic due to the instability of block formation and

limitations on data processing and storage. To create an IoT

security infrastructure, IoT organizations must work together,

coordinate, and integrate. Blockchain can facilitate secure and

scalable environments for developing a distributed database and

consistent design, as well as promote smooth communication

and interaction among IoT devices. In general, blockchain

offers the potential to apply enhanced performance paradigms

for IoT and stop security assaults and privacy violations [94].

Velmurugadass et al. [95] proposed a blockchain architecture

for preserving provenance and gathering evidence in the cloud

Infrastructure as a service(IaaS). The system has real-time

implementations for user registration, authentication, data

encryption, data storage, and tracking user activity. Utilizing a

distributed design raises the system's security bar. The

suggested system makes use of the most recent algorithm,

which delivers the best outcomes with minimal processing cost.

The validity of the evidence acquired and user privacy are both

increased by the investigator's ability to mine data from the

Software Defined Networking(SDN) controller and the

blockchain to ascertain who has altered the evidence. The

proposed system performs better in terms of response time and

total change rate, according to experimental results.

Kumar et al. [96] described a new Privacy-Preserved Threat

Intelligence Framework (P2TIF) that protects industrial data

while efficiently detecting harmful activity in IIoT networks

through the use of deep learning and blockchain technology.

The framework is composed of an InterPlanetary File System

(IPFS) distributed storage system for scalability and a

blockchain module for recording and validating transactions

using smart contracts. For threat detection, there is also a Deep

Learning module with an Attention-based Deep Gated

Recurrent Neural Network and a Deep Variational Auto

Encoder. The proposed strategy outperforms state-of-the-art

studies and prior privacy-preserving TI approaches. Future

evaluations of the usefulness and scalability of the Privacy-

Preserved Threat Intelligence Framework (P2TIF) framework

will make use of a micro service architecture, among other

things.

Shahbazi et al. [97] described the efficacy of multistage

quality control employing blockchain-based and machine

learning methods. By extracting complex associations from the

dataset, XGBoost was discovered to be the algorithm that

provides quality evaluation with the greatest accuracy.

Blockchain and machine learning integration enhances

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content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

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corporate environments with increased safety and trust while

also providing a secure environment for smart manufacturing.

The system produced good results, and as part of subsequent

study, the network size will be raised to test its efficacy in

industrial environments with more intricate setups.

Thakor et al. [98] discussed IoT security challenges resulting

from the exponential development in IoT devices that have led

to the demand for efficient, lightweight techniques to secure

IoT devices. The report analyzes the precisely described

Lightweight Cryptography (LWC) National Institute of

Standards and Technology(NIST) features and identifies

research problems and gaps. Due to security considerations, the

study endorses PRivacy ENhanced Solitaire Evaluation against

Network Threats(PRESENT) and CLEFIA as the accepted

block ciphers by NIST, whereas SIMON and SPECK are

praised for their compact implementations. Here PREDENT,

CLEFIA, SIMON and SPECK are the block cipher algorithms.

No LWC algorithm, however, satisfies all hardware and

software performance characteristics, and new assaults are

documented as the number of LWC algorithms increases. This

emphasizes the necessity of continued study in the area of

cybersecurity, particularly light cryptography.

Kumar et al. [99] presented an intelligent blockchain

architecture known as the Privacy Preserving and Secure

Framework (PPSF) that integrates machine learning techniques

has been developed. In order to achieve more efficient privacy

protection, the system incorporates a PCA-based

transformation technique for changing data into a new format

and an ePoW technique for evaluating data integrity based on

blockchain and smart contracts. Additionally, the framework

has a Gradient Boosting Anomaly Detector-based LightGBM

for intrusion detection. The privacy-preserving intrusion

detection approaches currently in use are outperformed by the

proposed IoT-cloud-fog-blockchain-IPFS architecture. We will

make a prototype in the future to test the usability of the

framework.

B. DATA MANAGEMENT AND MONETIZATION

1) DATA MARKETPLACES AND MONETIZATION

Data Marketplaces and Monetization: Blockchain can facilitate

the creation of decentralized data marketplaces where IoT

device owners can securely share and monetize their data.

Blockchain-based smart contracts can automate data

transactions and ensure fair and transparent compensation for

data providers.

IoT data marketplaces and data trading/marketplaces use

blockchain technology to facilitate safe, transparent

transactions for the purchase and sale of data. Dataset owners

publish their offerings, and smart contracts control terms like

price and quality. Blockchain transactions are started by buyers

and are confirmed by consensus to build confidence. Smart

contracts automatically deliver data to buyers and pay sellers

with cryptocurrency if they are validated. Security is ensured

by the blockchain's immutable recording of details, including

data, agreements, and payments. Fairness and security are

enhanced by decentralized government, which does away with

central authority. Parties examine the blockchain record for

transparency and dispute resolution after the transaction.

Essentially, the procedure entails data listing, smart contract

creation, blockchain transaction initiation, consensus

validation, data access and payment transfers, blockchain

recording, and decentralized governance to enable safe and

transparent IoT data trading [174].

González et al. [100] discussed a Blockchain-based IoT

Data Marketplace (BIDM), which enables decentralized and

transparent exchange of information between IoT

infrastructures and applications. BIDM ensures the traceability

of data transactions, authenticates data sources, and ensures

platform reliability. Performance evaluations demonstrate that

BIDM has minimal impact on measurement registration and

purchase procedures, while also exhibiting high scalability and

streamlined operation under heavy loads. The paper addresses

key research questions related to BIDM's architecture,

functionalities, scalability, and performance. It highlights the

potential of properly integrating Blockchain technologies to

support flexible and trustworthy data exchange in IoT

marketplaces.

Christidis et al. [101] conducts a comprehensive review of

existing works on decentralized IoT data marketplaces, with a

focus on design factors. The analysis reveals that none of the

reviewed works fully address all the requirements for a

decentralized IoT marketplace, indicating the need for new

designs. Most of the reviewed works utilize smart contract-

compatible blockchains, but there is a call for maximizing smart

contract usage while considering cost efficiency in future

implementations.

Khezr et al. [102] proposed a secure and dependable system

that combines blockchain and fog computing for IoT data

trading. Leveraging fog crowd sourcing nodes, the system

facilitates the aggregation and transmission of IoT data,

enabling quick decision-making, edge device maintenance, and

reduced latency. Through the incorporation of blockchain, the

system ensures secure data management, authentication,

ownership, and high dependability. The system design and

evaluation consider important performance parameters such as

transaction throughput, elapsed time, and resource

consumption. Future plans involve scaling up the system,

addressing challenges related to secure smart contract creation,

and optimizing algorithms to enhance efficiency.

Özyilmaz et al. [103] develops a decentralized data

marketplace for non-critical, non-real time IoT applications by

building on prior research. The marketplace aspires to

democratize access to authorized data for the benefit of end

users, AI/ML service providers, and makers of IoT devices.

With Swarm serving as the storage system, the proof-of-

concept market is constructed using Ethereum smart contracts.

It features various querying options and a voting system to

weed out dubious data sources. The smart contract code, known

as "IDMoB: IoT Data Marketplace on Blockchain," is openly

accessible on GitHub and serves as a starting point for

additional research and advancement in this area.

2) INTEROPERABILITY AND DATA EXCHANGE

Interoperability and Data Exchange: Blockchain can enable

secure and standardized data exchange between different IoT

devices and platforms. The integration of blockchain

technology with the Internet of Things (IoT) requires

prioritizing interoperability and data interchange. This involves

using adapters for various communication protocols, utilizing

standardized protocols like Message Queuing Telemetry

Transport (MQTT), Constrained Application Protocol (CoAP),

or Hypertext Transfer Protocol (HTTP), and connecting

blockchain networks using Ethereum and Hyperledger

standards. Smart contracts set transaction criteria and secure

data exchange terms, while decentralized identity management

and cryptographic algorithms ensure data encryption. Constant

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

analytics and monitoring are crucial for a strong integration. It

provides a trusted framework for data sharing, removing the

need for intermediaries and enhancing interoperability across

diverse IoT ecosystems [175].

Li et al. [104] proposes a blockchain-based program for the

IoT that rewards private data sharing. The plan guarantees

anonymity, eliminates framing, and hinders the development of

behavior profiles. Access control is made possible through

smart contract-generated licenses and the blockchain, which

assures transaction anonymity. Data users' privacy is

guaranteed through deniable ring signatures and Monero.

Performance study demonstrates the scheme's efficacy, while

formal security proofs indicate how secure it may be proved to

be. Key distribution, anonymous authentication, and scalability

in IoT data-sharing systems will be the main topics of future

research.

Shen et al. [105] introduces MedChain, a patient-driven

healthcare data-sharing platform that increases effectiveness

without sacrificing security. The framework uses a digest chain

structure, a dual-network architecture, and session-based data

exchange. Gradual integration with current systems and the

addition of data streams from tracking devices improve

scalability and are advantageous to researchers, medical

professionals, and healthcare providers. Solutions for data

transportation, easy data sharing, and effective information

uploading are other advancements.

Xie et al. [106] proposed that data security and identity

security are addressed in IoT data sharing using the TEE-and-

Blockchain-supported IoT data sharing (TEBDS) architecture,

which combines on-chain and off-chain techniques. While off-

chain data is secured by an Intel SGX-based Distributed Storage

System (SDSS), on-chain data is protected and access is

controlled using a consortium blockchain. Security study shows

that the system has a motivational mechanism and satisfies

security standards. According to experimental findings,

centralized methods perform better.

C. DEVICE MANAGEMENT AND UPDATES

1) OVER-THE-AIR (OTA) UPDATES

Over-the-Air (OTA) Updates: Blockchain can enhance the

security and reliability of OTA updates for IoT devices. By

using blockchain, software updates can be securely distributed,

and the integrity of the update can be verified using

cryptographic mechanisms.

Alqahtani et al. [107] presents a permissioned blockchain

system for securing OTA firmware updates in IoT devices. It

replaces centralized solutions and works well in diverse

environments with multiple devices and vendors. The system

ensures integrity through authentication and security measures,

while smart contracts enforce firmware update terms. A

successful proof-of-concept using Hyperledger Fabric,

Chaincode, and the Wemos D1 Mini board demonstrates

feasibility, efficiency, and strong cybersecurity. The system

scales effectively and smart contracts provide flexibility.

Resilience against DoS and MitM attacks validates smart

contract preservation. Future work includes expanding device

compatibility, intelligent smart contract creation, and improved

system monitoring.

2) DISTRIBUTED DEVICE MANAGEMENT

Distributed Device Management: Blockchain can decentralize

the management and control of IoT devices. It allows for

distributed consensus and decision-making processes, enabling

secure device management, configuration, and firmware

updates without relying on a central authority. The principles of

decentralized storage prioritize immutability, security, and

transparency, which are in line with the characteristics of

blockchain technology. Data integrity is guaranteed by the use

of cryptographic algorithms, and security is further enhanced

by distributed storage, which reduces the risk of single points

of failure. Furthermore, a publicly accessible record preserves

clarity and verifiability, which is essential for ensuring

responsibility. Decentralized storage in IoT data management

provides advantages such as data integrity, privacy, and

scalability. Data redundancy guarantees the continuous

accessibility of data, encryption safeguards confidentiality, and

scalability allows for the handling of increasing amounts of

data. Decentralized storage ultimately improves dependability

and availability while staying in line with the fundamental

principles of blockchain technology [26].

Distributed file systems like IPFS or decentralized cloud

storage options enable security, privacy and control.

Decentralized storage solutions enhance security by employing

data encryption, decentralized architecture, and immutable data

structures, which guarantee confidentiality, resilience, and data

integrity. Furthermore, privacy is enhanced through the

distribution of ownership, anonymous access, and the use of

zero-knowledge proofs, enabling users to have control over

who can access their data while maintaining anonymity.

Furthermore, users retain complete control and implement

detailed access restrictions, promoting openness and

responsibility in data administration. Transparent governance

methods bolster user trust and confidence, fostering a

community-led approach to decentralized storage[186].

Reijsbergen et al. [108] introduced a compact blockchain

framework to guarantee the reliability of the firmware and data

in IoT sensor networks. The system offers protection methods

that address scalability and deploy ability issues that were

identified through a thorough threat model. These measures

include a two-layer blockchain, examination of threats that

target blockchains specifically, and cutting-edge threshold

signatures. Stress testing for the use of smart contracts in

Ethereum and Hyperledger Fabric were successful. The

Feather-LightBlockchainInfrastructure (FLBI) framework is

appropriate for a variety of IoT contexts since it provides better

security and auditable smart contract code.

Tsaur et al. [109] proposed mechanism leverages blockchain

for multi-node verification of IoT firmware, enhancing device

security. It proposes a distributed database to store firmware

information, guaranteeing correctness and integrity. By

downloading firmware through the distributed database instead

of relying on manufacturers' servers, the burden is reduced, and

tampering is prevented. Future research aims to implement a

revocation function for expired IoT firmware, further

improving the mechanism.

Choi et al. [110] proposed a blockchain-based decentralized

architecture for safe firmware updates in IoT devices. It

guarantees network load distribution and upholds the accuracy

of firmware images. The architecture includes retrieval nodes

for downloading as well as registration nodes for processing

firmware and manifest files. It fixes problems with author-

disappearing and server targeting. Future work entails

developing precise messaging methods, putting the architecture

into practice on consortium and private blockchains, and

performing security and performance studies.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

D. BUSINESS AGREEMENTS AND COMPUTING

1) SERVICE-LEVEL AGREEMENTS (SLAs) AND

PAYMENTS

Blockchain can facilitate the implementation of Service Level

Agreements (SLAs) between IoT device providers and

consumers. Smart contracts on the blockchain can automate the

verification of service delivery, trigger payments based on

predefined conditions, and resolve disputes in a transparent and

auditable manner.

Saputhanthri et al. [111] examines the difficulties IoT

applications encounter, and if blockchain-based solutions are

appropriate for resolving such difficulties. It focuses on

blockchain-enabled IoT payment transactions and markets for

data sharing. In IoT application domains such as smart

manufacturing, smart agriculture, Internet of Vehicles (IoVs),

smart health, and content trading, promising outcomes have

been seen. However, for blockchain to fully realize its promise

in IoT, integration difficulties like transaction fees, scalability,

security and privacy, and quantum resistance need to be

overcome.

Tan et al. [112] introduced a workable SLABSC

management strategy that addresses the Slack Service Level

Agreement model by integrating Blockchain and Smart

Contract (SLABSC) management in cloud computing using

blockchain and smart contracts. The approach offers methods

for punishment and enables prompt detection of infractions. It

increases interparty confidence, safeguards data security, and

gives administrators the authority to oversee cloud service

providers (CSPs). Performance of the suggested approach has

been confirmed, and as Blockchain technology develops, more

gains are anticipated.

Zheng et al. [113] proposed SLA management in Blockchain

as a Service (BaaS) systems using a consensus mechanism

based on K-nearest neighbor (KNN). It gives high-priority

transactions quick handling even if they arrive late by

prioritizing them according to their urgency. The algorithm

raises SLA fulfillment between cloud service providers (CSPs)

and cloud service consumers (CSCs). The experimental

findings highlight the benefits of the suggested approach, and

subsequent study will focus on investigating other features and

classification strategies.

Weerasinghe et al. [114] introduced a Novel Consensus

Mechanism for Secure Service Level Agreement (SSLA)

Management on Blockchain: In this study, an automated SSLA

management system using a unique blockchain technology

called PoM consensus is presented. When compared to PoW

consensus, the suggested solution saves time, energy, and

money. It performs better than other platforms in terms of

security features and provides acceptable end-to-end latency.

Off-chain databases are used to boost performance, scalability,

and adaptability. Future development will concentrate on

extending the implementation and utilizing AI-based solutions.

Potential application cases have been discovered.

2) EDGE COMPUTING AND FOG COMPUTING

Blockchain can enable decentralized data processing and

analytics at the network edge by combining with edge and fog

computing models. By processing sensitive data locally rather

than transferring it to a central cloud server, this can increase

efficiency, decrease latency, and improve privacy.

Xue et al. [115] explores the securing resource management,

offloading computations, and data sharing through the use of

edge computing, blockchain technology, and Internet of Things

applications. Research issues pertaining to data management,

compute offloading, security, privacy, and resource

management are discussed. The challenges and performance

optimisation of the blockchain and edge computing (IBEC)

technology are observed.

Ajao et al. [116] proposed a Blockchain-Based Machine

Learning - Intrusion Detection System (BML-IDS) framework

to protect networks for sustainable smart city fog computing.

Data flow is detected and secured using blockchain and

machine learning algorithms. The outcomes demonstrate

outstanding detection precision and quick processing. Deep

learning and optimization methods for intrusion detection will

be explored in future research.

Guo et al. [117] presents a multi-factor integrated blockchain

and Ciphertext policy attribute based encryption (CP-ABE)

data sharing system for Vehicular Fog Computing (VFC). It

guarantees effective attribute revocation, targeted data access

based on user characteristics and interests, and distributed

cooperative storage. In terms of usefulness and security, the

suggested approach performs better than those now in use, but

future research will examine additional elements to make it

more adaptable and practical.

The deep literature review has identified some research gaps

as shown in Table 4.

TABLE 4. Literature review

Reference

Contribution

Architecture/Technique Used

Limitation/Research Gap

[118]

Robust security systems for IoT-based

smart environments

Use of IDS systems, secure

ICSs

Confidentiality, integrity, availability

issues, challenges of accurate detection and

intrusion evasion.

[119]

Blockchain-based IoT Data Marketplace

for decentralized and transparent data

exchange

BIDM platform

Evaluation conducted on heavy loads, need

for extending evaluation to other

performance metrics and aspects.

[120]

Framework for enhancing IoT network

security through ML-based IDSs

HBFL framework

Scalability issue in terms of large no. of IoT

devices, computational resources,

communication overhead, and

performance..

[121]

Framework for addressing security

challenges in IoT systems using BC

managers

Interoperability between BC

managers, FSSM MS manager

Paper doesn't provide details about the

specific security and privacy challenges

addressed by the framework.

Interoperability between heterogeneous

blockchain networks is missing.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

[122]

Utilization of blockchain in healthcare

systems to provide safe data

Access control policy system

architecture

Scalability problem, as the number of users

and transactions grows, the system may

encounter performance problems and

experience slower transaction processing

times.

[123]

Discussed security challenges facing IoT

applications and explored security

solutions using blockchain technology, fog

computing, and machine learning

Blockchain,Fog Computing,

Machine Learning

Lightweight security protocols and

algorithms like ECC-based algorithms for

IoT devices due to their resource constraints

were not considered.

[124]

Provided a comprehensive overview of

security attacks on IoT devices and

discussed various IoT solutions, including

machine learning, blockchain, and edge

computing

Machine Learning, Blockchain,

Edge Computing

Focuses on solutions but not provide

enough information on the limitations and

potential drawbacks of these solutions

[125]

Discussed how integrating blockchain with

IoT might increase the stability and

dependability of information and systems

as well as avoid security assaults and

privacy violations.

Blockchain

To create an IoT security infrastructure, IoT

organizations must work together,

coordinate, and integrate.

[126]

Proposed a blockchain architecture for

preserving provenance and gathering

evidence in the IaaS cloud.

Blockchain

Provides limited security analysis

[127]

Provided details of a new Privacy-

Preserved Threat Intelligence Framework

for detecting harmful events in IIoT

networks.

Attention-based Deep Gated

Recurrent Neural Network,

IPFS, Deep Variational

AutoEncoder

Evaluation of the P2TIF framework's

scalability and usefulness utilizing a micro

service architecture is required.

[128]

Examined the effectiveness of multistage

quality control using machine learning and

blockchain-based solutions

XGBoost, Blockchain

Performance of the system in more

complicated manufacturing environments

needs to be tested

[129]

Discussed the usefulness of implementing

blockchain technology in IoT systems to

produce, store, and transfer digital assets in

a safe and incorruptible way.

Fog computing, Cloud

computing, Blockchain

Network latency is the dominant factor

affecting performance when using fog and

cloud computing as hosting platforms for

BaaS

[130]

With an emphasis on machine learning

(ML)-based techniques for mitigating

attacks on IoT networks, we examined

recent literature on assaults and their

responses in the context of the Internet of

Things (IoT).

Industrial Control Systems,

Industrial IoT (IIoT), PASTA

threat model, hybrid

approaches, signature-based,

anomaly-based, and ML

algorithms

Protecting IoT networks from APT attacks

and unresolved concerns and obstacles for

network infiltration based on ML

approaches are not addressed.

[131]

An analysis of existing research on IoT

vulnerabilities was conducted.

IoT technologies

Lack of Internet-scale solutions addressing

the problem of IoT resilience

Access control and authentication are the main topics of current

research on blockchain-based IoT security systems. Research

on the integration of blockchain with other security

mechanisms, like intrusion detection and prevention systems, is

needed to increase the general security of IoT devices. In order

to fill this research gap, the proposed study would create a

thorough blockchain-based security framework for IoT-enabled

smart environments.

V. LIMITATIONS AND CHALLENGES FOR BLOCKCAHIN IN IOT

BASED ENVIRONMENT

A. BLOCKCHAIN SCALABILITY IN IoT

In the IoT ecosystem, scaling is a significant difficulty because

the increasing volume of devices and transactions may cause

processing lags and bottlenecks. Blockchain IoT integration is

challenging due to resource limitations and scalability

difficulties. A number of solutions have been put out to address

this issue, including Segwit, sharding, block size expansion,

PoS, and off-chain state. To improve scalability, Ethereum

developers are actively working to introduce DAG and sharding

[132].

The integration of blockchain technology with the Internet

of Things (IoT) presents a significant problem in terms of

scalability. This challenge stems mainly from the vast amount

of data generated by a variety of IoT devices and the limitations

of conventional blockchain topologies. Because consensus

techniques like proof-of-work intrinsically slow down

transaction speed, traditional networks like Bitcoin and

Ethereum struggle to handle the massive inflow of data from

multiple IoT devices. Challenges also arise from block size and

frequency; huge blocks and longer block durations slow down

transaction processing and may result in bottlenecks. As the

blockchain network experiences increased usage and more IoT

devices submit transactions at once, network congestion

becomes an issue that could cause delays and potentially

impede real-time applications. Furthermore, proof-of-work-

based consensus procedures, which are resource-intensive, can

be computationally demanding and present difficulties for IoT

devices that have limited processing capacity and energy

resources. Moreover, the increasing amount of data generated

by Internet of Things devices increases the amount of storage

that the blockchain needs, which raises questions regarding

storage costs and network participants' capacity to oversee and

verify the growing blockchain data [176].

• SCALABILITY SOLUTIONS: Scalability solutions are crucial

in solving the performance issues associated with blockchain

implementations in IoT contexts. Sharding is the process of

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

dividing the blockchain into smaller subsets known as shards to

make it more manageable. Every shard has the responsibility of

handling a specific fraction of the total transaction load, which

allows for parallel transaction processing and enhances

throughput. Sharding improves the scalability of blockchain

networks by splitting the computational workload among

numerous shards. This allows the networks to handle a greater

number of transactions without sacrificing efficiency. In

addition, off-chain storage solutions address scalability

concerns by transferring certain data and processing tasks away

from the primary blockchain network. This may involve the

storage of transaction data or the execution of smart contracts

on auxiliary layers, such as sidechains or state channels, prior

to finalizing the outcomes on the primary blockchain. Off-chain

storage solutions alleviate the load on the main chain,

enhancing the speed and responsiveness while upholding the

integrity and security of data. By elucidating the ways in which

sharding and off-chain storage address scalability issues,

readers can gain a more profound comprehension of the

intricate tactics implemented to enhance blockchain

performance in IoT applications [177][178].

B. SECURITY AND PRIVACY

Security is a crucial concern when implementing blockchain in

the IoT. IoT devices are susceptible to assaults because they

frequently have low processing and memory capacities.

Additionally, blockchain's public and immutable nature may

expose sensitive data from IoT devices. Ensuring secure

communication, authentication, and data encryption becomes

essential to protect IoT devices and maintain privacy.

Mohanta et al. [179] study highlights the privacy challenges

of integrating blockchain technology with the Internet of

Things (IoT). The transparency and immutability of blockchain

technology can expose sensitive data to all network users,

potentially violating privacy laws. The pseudonymous nature of

transactions raises issues over device identification and privacy.

Controlling user consent and ensuring data access is

challenging, emphasizing the need for privacy-aware solutions

Liu et al. [133] discussed rapid growth of smart homes has

resulted in a variety of smart devices from different vendors,

making centralized solutions challenging. Blockchain offers

potential solutions, but scalability is a major issue. This study

proposes Community chain, a scalable blockchain architecture

for smart homes, utilizing a community model based on

sharding, efficient routing, and side Block schemes. It also

ensures secure access through lightweight authorization and

authentication processes. Experimental results show that this

architecture improves scalability and adapts well to system

dynamics.

Pabitha et al. [134] offers methods for developing a

decentralized, scalable, and secure IoT blockchain framework,

with a focus on scalability issues and quick transaction

confirmation. The proposed ModChain incorporates an

incentive and deposit mechanism for fairness, a node

committee, a leader election mechanism, and a modified

consensus algorithm. These integrations improve blockchain

throughput while maintaining security. A Private Auction

Mechanism is proposed for scalability, outperforming

Randomized Selection in transaction speed. Further research

can explore the mechanism's performance in outlier cases and

expand the Anti-takeover mechanism to address other attack

vectors.

Tang et al. [135] In order to improve IoT security and

privacy, this article considers incorporating blockchain into

the Multi-access Edge Computing (MEC) network. It

suggests a permission-less, scalable consensus mechanism

named "Hedera" that combines asynchronous Byzantine and

proof-of-capacity techniques. The experimental results

demonstrate fairness, high throughput (13986.3 TPS), and

low resource consumption compared to PoW consensus. The

algorithm is also resilient against various attacks, ensuring

security and liveness in the Multi-access edge computing

(MEC) network.

C. CONSENSUS MECHANISMS AND LATENCY

Blockchain networks' consensus algorithms control how

transactions are verified and added to the blockchain. Proof-of-

Work (PoW) is a common consensus mechanism, but it can be

resource-intensive and have high latency [180][184]. Long

confirmation times and significant energy use may not be

practical in an IoT context where real-time responsiveness is

essential. It can be difficult to create consensus algorithms that

are both effective and portable for IoT devices.

The diversity of IoT devices, each with distinct

computational capabilities, energy limits, and communication

protocols, presents consensus issues in blockchain IoT

integration. Energy-intensive consensus processes, a range of

computational capabilities, conflicts in real-time processing,

scalability issues, security trade-offs, decentralization

difficulties, interoperability problems, and the requirement for

fault tolerance are some of the hurdles[184]. To address latency

in IoT devices, energy-efficient consensus mechanisms like

proof-of-stake [23] can be implemented. Optimizing consensus

for limited resources and exploring scalability options like

sharding [177] can also be considered. Balancing security and

efficiency, decentralization, interoperability, and fault-tolerant

mechanisms is crucial. Robust blockchain consensus

mechanisms require hybrid models and tailored solutions[185].

D. LEGAL AND REGULATORY CHALLENGES

Integrating blockchain with IoT raises legal and regulatory

concerns. Data ownership, privacy, and compliance with

existing laws and regulations can be complex in decentralized

systems. Establishing a legal framework and addressing

jurisdictional issues becomes crucial to ensure the legality and

accountability of IoT blockchain applications.

Researchers and industry specialists are actively working to

address these difficulties. Efforts are being made to address

these limitations through the exploration of solutions such as

layer 2 scaling techniques (e.g., sidechains[178]), privacy-

enhancing technologies, lightweight consensus algorithms

(e.g., Proof-of-Stake [23], Directed Acyclic Graphs[29]), and

collaborations between technology and legal domains [185].As

shown in Table 5. there are several open issues and challenges

related to the use of blockchain in IoT-based smart

environments. These include scalability, interoperability,

privacy and security, energy efficiency, governance, and

regulatory compliance. Additionally, there are limitations

related to the adoption and integration of blockchain

technology, such as high costs and the need for specialized

technical expertise.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

TABLE 5. Open issues and challenges

Issues and Challenges

Solutions to Address Them

Future Scope of Blockchain

Reference

Lack of scalability and slow

transaction processing speed

Implementing sharding, sidechains, and layer 2

solutions

Developing faster and more efficient

consensus algorithms

[136]–[138]

Security threats, including 51%

attacks and hacks

Implementing advanced cryptography and

security protocols

Integrating artificial intelligence and

machine learning to enhance security

[139] [140]

Regulatory challenges and legal

frameworks

Developing clear and consistent regulations for

blockchain

Creating international standards and

collaborations

[141]

Interoperability and compatibility

issues

Developing standardized protocols for

blockchain interoperability

Integrating blockchain with other emerging

technologies, such as IoT and AI

[142]

Energy consumption and

environmental impact

Implementing energy-efficient consensus

algorithms and renewable energy sources

Developing eco-friendly blockchain

solutions

[143]

VI. CONCLUSION AND FUTURE DIRECTION

The future directions and challenges for blockchain in IoT-

based environments include the implementation of smart

contracts to automate contractual obligations, addressing

scalability issues, and privacy and security concerns due to

sensitive data generated by IoT devices. Integration with

emerging technologies like AI and ML can also offer

opportunities for innovation, and blockchain governance,

standardization, and interoperability are critical for adoption in

IoT environments. Blockchain technology combined with AI

and ML ensures safe, open data processes that build confidence.

Smart contract automation improves productivity, and

decentralized execution makes AI and ML applications

collaborative and scalable, which builds the groundwork for

creative and open ecosystems.Adoption and implementation in

various industries like healthcare, finance, and supply chain

management can provide insights into blockchain's potential

impact. Overall, future research can explore the potential of

blockchain in addressing challenges and providing new insights

into its applications and implementation. This review paper

highlights the potential impact of blockchain technology on

IoT-based environments. It covers the fundamental aspects of

blockchain, including its architecture, taxonomy, types, core

components, and distributed ledger technology. The paper also

discusses the various layers of blockchain, its key

characteristics, and its different application areas. The

challenges and limitations of blockchain technology, such as

scalability and interoperability, are also presented, along with

the future scope of research in this area. Overall, this review

provides a comprehensive understanding of blockchain's

potential to revolutionize IoT-based environments while

addressing the challenges of widespread adoption.

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1. Deepak completed his MSc from M. D.

University, Rohtak. He is currently

pursuing a Ph.D. in Computer Science at

the Department of Computer Science &

Applications, M.D. University, Rohtak,

India. His main research area includes the

Internet of Things (IoT), Blockchain Technology and

Machine Learning. He can be contacted at

email: deepak.rs23.dcsa@mdurohtak.ac.in, ORCID

ID: 0009-0006-0311-0207.

2. NASIB SINGH GILL holds post-

Doctoral research in Computer Science

at Brunel University, West London

during 2001-2002 and Ph.D. in

Computer Science in 1996. He is a

recipient of the Commonwealth

Fellowship Award of the British

Government for the Year 2001. Besides, he also has earned

his MBA degree. He is currently Head of the Department of

Computer Science & Applications, M. D. University,

Rohtak, India. He is also working as Director of the

Directorate of Distance Education as well as Director of the

Digital Learning Centre, M. D. University, Rohtak, Haryana.

He is an active professional member of IETE, IAENG, and

CSI. He has published more than 304 research papers

indexed in SCI, SCIE, and Scopus and authored 5 popular

books He has guided so far 12 Ph.D. scholars as well as

guiding about 5 more scholars. His research interests

primarily include – IoT, Machine & Deep Learning,

Information and Network Security, Data mining & Data

warehousing, NLP, Measurement of Component-based

Systems, etc. He can be contacted at email:

nasib.gill@mdurohtak.ac.in, ORCID: 0000-0002-8594-

4320.

3. PREETI GULIA received a Ph.D.

degree in computer science in 2013. She

is currently working as an Associate

Professor at the Department of Computer

Science & Applications, M.D. University,

Rohtak, India. She is serving the

Department since 2009. She has published

more than 80 research papers indexed in SCI, SCIE, and

Scopus and presented papers in national and international

conferences. She has guided 04 scholars and guiding 05

more scholars. Her area of research includes Data Mining,

Big Data, Machine Learning, Deep Learning, IoT, and

Software Engineering. She is an active professional member

of IAENG, CSI, and ACM. She is also serving as an Editorial

Board Member and Active Reviewer of International/

National Journals. She can be contacted at email:

preeti@mdurohtak.ac.in, ORCID: 0000-0001-8535-4016.

4. Mohammad Yahya is a Senior

Software Engineer and Deep Learning

Architect. He holds a PhD in Computer

Science from Oakland University, with

his dissertation focusing on programming

languages for clone detection systems.

He also obtained an MS in Computer Science with a minor

in Machine Learning from Harbin Institute of Technology.

yahya@oakland.edu.

https://orcid.org/0000-0001-9686-3385.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

VOLUME XX, 2023 9

5. Punit Gupta is Post-Doctoral

Researcher at University College Dublin,

Ireland. He received B.Tech. Degree in

Computer Science and Engineering from

Rajiv Gandhi Proudyogiki

Vishwavidyalaya, Madhya Pradesh in

2010. He received M.Tech. Degree in Computer Science and

Engineering from Jaypee Institute of Information

Technology (Deemed University) in 2012 On "Trust

Management in Cloud computing". He is a Gold Medalist in

M-Tech. He has been awarded doctoral degree in Feb 2017.

Guest Editor: Scientific computing, Journal Recent

Advances in Computer Science and Communications,

punit.gupta@ucd.ie.

6. Prashant Kumar Shukla, Associate

Professor (Research), Department of

Computer Science and

Engineering, Koneru Lakshmaiah

Education Foundation, Vaddeswaram,

Guntur - 522302, Andhra Pradesh,

India, prashantshukla2005@kluniversity.in, Orcid:

0000-0002-3092-2415.

Prashant Kumar Shukla received his Master of Engineering

in Software Systems from RGPV, Bhopal, Madhya Pradesh

in 2010 and Ph.D. (Computer Science & Engineering) in

2018 from Dr. K. N. Modi University, Rajasthan, India.

Presently, he has been working as an Associate Professor

(Research) in the Department of Computer Science and

Engineering, Koneru Lakshmaiah Education Foundation,

Vaddeswaram, Guntur, Andhra Pradesh, India from October

2021. He has also worked as an Assistant Professor (SG) and

Research Coordinator in Jagran Lakecity University, Bhopal

(MP) India from July 2019 to September 2021. He has also

worked as Associate Professor in SISTec, Bhopal (MP) from

Jan 2019 to July 2019 and as Associate Professor in SIRT,

Bhopal (MP) India from 2011 to 2019. He has been in

teaching, research, innovation and industry for the past 16

years and working in the research areas like Artificial

Intelligence, Machine Learning, Deep Learning, Data

Science, Computer Vision, Internet of Things (IOT)

concerns. He has been granted 08 patents. He has been

published 28 Indian patents and one Indian Copyright is

granted. He has been worked for tuning India project, Co-

funded by the Erasmus+ Programme of the European Union

and coordinated by University of Deusto, Bilbao, Spain. He

has received funding for 2 research projects from Govt. He

has published 37 research papers in SCI (Science Citation

Index), 12 papers in Scopus indexed and 11 papers in peer

reviewed journals and conferences. He has also published 02

Chapters in Scopus indexed edited book.

7. Dr. Piyush Kumar Shukla (PDF, Ph.D.,

SMIEE, LMISTE) is Associate Professor in

Computer Science & Engineering Department,

University Institute of Technology, Rajiv

Gandhi Proudyogiki Vishwavidyalaya

(Technological University of Madhya Pradesh). He has

completed Post Doctorate Fellowship (PDF) under

"Information Security Education and Awareness Project Phase

II" funded by the Ministry of Electronics and IT (MeitY). He is

the editor and reviewer of various prestigious SCI, SCIE, and

WOS-indexed journals. He has over 300 publications in highly

indexed journals and prestigious conferences, including many

books, piyush@rgpv.ac.in.

This article has been accepted for publication in IEEE Access. This is the author's version which has not been fully edited and

content may change prior to final publication. Citation information: DOI 10.1109/ACCESS.2024.3366656

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/

Blockchain-enhanced electoral integrity: a robust model for secure digital voting systems in Oman

Article

Apr 2025

Background Ensuring the security and trustworthiness of a digitized and automated electoral process remains a significant challenge in democratic systems. As digital voting systems are increasingly being investigated worldwide, ensuring the integrity of the process using robust security measures is of great importance. This paper presents a simplified model to enhance electoral integrity by leveraging Blockchain technology in the context of Oman’s digital voting system. The model uses Blockchain technology to create a secure and trustworthy voting environment, addressing key vulnerabilities in digital electoral systems. Methods The research utilized a quantitative approach, employing an experimental design methodology using open-source software to simulate voting systems. Synthetic population data is used to operate these systems, while advanced biometric authentication technologies verify voter identities. Blockchain technology is leveraged to ensure secure vote recording, with smart contracts used to authenticate voters and securely record votes. Additionally, synchronous transactions are executed for both voter registration and voting processes, enhancing the overall security and efficiency of the system. Results The experimental results show that Blockchain enhances electoral integrity and security in Oman’s voting system, improving elections’ transparency and reliability. The performance evaluation of the model focuses on efficiency, reliability, and scalability metrics. Asynchronous transactions are utilized to improve processing time for voter registration and voting. Election administrators can manage, monitor, and certify election results, while Ethereum nodes ensure decentralized verification and transparency in the voting process. Conclusion This research offers insights for policymakers to consider Blockchain for electoral reforms, addressing issues like data integrity, fraud prevention, and transparency to boost voter trust. A strong regulatory framework and public awareness are crucial for successful implementation. Pilot projects are needed to assess Blockchain’s practical impact. Oman could lead global innovation in electoral technology, though infrastructure and public resistance challenges must be managed.

Exploring blockchain solutions: Integrating cryptocurrency with IoT for enhanced security

Conference Paper

Apr 2025

Blockchain, initially developed as the underlying technology for Bitcoin, has garnered significant attention for its applications beyond cryptocurrency, particularly in complex non-monetary domains. Utilizing cryptographic methods like hashing and asymmetric encryption, combined with a distributed consensus model, Blockchain-based ledgers achieve high levels of security and immutability, effectively removing the need for third-party intermediaries. Meanwhile, the rapid growth in Internet of Things (IoT) devices being connected to networks raises substantial concerns around security and privacy. Addressing these security challenges is essential for the expanding IoT landscape. This paper explores the blockchain solution by integrating cryptocurrency with IoT for enhanced security, reviewing recent studies and applications to evaluate Blockchain's role in IoT security, pinpoint challenges, and propose Blockchain-driven solutions to improve security in the IoT ecosystem.

Blockchain-enhanced electoral integrity: a robust model for secure digital voting systems in Oman

Article

Full-text available

Feb 2025

Background Ensuring the security and trustworthiness of a digitized and automated electoral process remains a significant challenge in democratic systems. As digital voting systems are increasingly being investigated around the world, ensuring the integrity of the process using robust security measures is of great importance. This paper presents a simplified model to enhance electoral integrity by leveraging Blockchain technology in the context of Oman’s digital voting system. The model uses Blockchain technology to create a secure and trustworthy voting environment, addressing key vulnerabilities in digital electoral systems. Methods The research utilized a quantitative approach, employing an experimental design methodology using open-source software to simulate voting systems. Synthetic population data is utilized for operating these systems, while advanced biometric authentication technologies are used to verify voter identities. Blockchain technology is leveraged to ensure secure vote recording, with smart contracts used to authenticate voters and securely record votes. Additionally, synchronous transactions are executed for both voter registration and voting processes, enhancing the overall security and efficiency of the system. Results The experimental results shows that Blockchain enhances electoral integrity and security in Oman voting system, improves transparency and reliability in elections. The performance evaluation of the model focuses on efficiency, reliability, and scalability metrics. Asynchronous transactions are utilized to improve processing time for voter registration and voting. Election administrators can manage, monitor, and certify election results, while Ethereum nodes ensure decentralized verification and transparency in the voting process. Conclusion This research offers insights for policymakers to consider Blockchain for electoral reforms, addressing issues like data integrity, fraud prevention, and transparency to boost voter trust. A strong regulatory framework and public awareness are crucial for successful implementation. Pilot projects are needed to assess Blockchain’s practical impact. Oman could lead global innovation in electoral technology, though infrastructure and public resistance challenges must be managed.

Integrating AI With Blockchains for Securing Cloud-Based IoT Networks: Benefits, Issues, and Challenges

Chapter

May 2025

IoT network is a collection of vast number of objects or devices which can sense and generate data for further processing that aids decision-making in real time applications. Connecting such IoT devices to cloud servers helps in faster and easier data storage and processing. Integrating Artificial Intelligence (AI) with Blockchain technologies is a potential solution for all the security threats in an IoT network. The IoT cloud has got its own limitations in terms of storage, bandwidth and is more likely to get affected due to malicious attacks happening at multiple layers of IoT architecture. This chapter examines the need for securing IoT cloud using blockchain technology and enhancements made to the same by integrating AI with Blockchain. The benefits due to this integration of technologies also bring in a few challenges which are discussed in this chapter.

Blockchain-enabled road vehicle emissions monitoring: A secure, scalable and private framework

Article

May 2025

Securing the internet of things communication and data transmission by using Blockchain based Architecture

Conference Paper

Jan 2025

Platform Design for Supply Chain based on Blockchain enabled IOT

Conference Paper

Nov 2024

Enhancing Internet of Things security using performance gradient boosting for network intrusion detection systems

Article

Mar 2025

A decentralised approach to cyber-physical systems as a service: Managing shared access worldwide through blockchain standards

Article

Feb 2025
COMPUT IND

Cyber-physical systems (CPSs) is a general concept that encompasses a wide variety of systems. Depending on their nature, application, and accessibility needs and restrictions, CPSs can differ a lot from each other. This paper proposes a classification of CPSs based on their accessibility needs and restrictions and, more importantly, presents an approach to create a decentralised and worldwide common access management framework for CPSs for non-critical infrastructures that are meant to be shared and accessed remotely (i.e., offered as a service). The presented solution uses a permissionless blockchain, existing fungible tokens, and a combination of smart contracts based on nonfungible token standards/proposals to enable CPS owners to manage secure, flexible access without centralised oversight. In addition, the proposed framework provides built-in mechanisms for: (i) charging for the use of CPSs, (ii) availability calendar configuration, (iii) worldwide visibility, (iv) easy integration with authentication/authorisation methods, and (v) access control flexibility.

A Survey on Enhancing Cloud Data Security Using Blockchain Technology

Conference Paper

Dec 2024

A blockchain-based security system with light cryptography for user authentication security

Article

Full-text available

Nov 2023
MULTIMED TOOLS APPL

Nowadays, the Internet of Things (IoT) enables the creation of a wide range of new services, including smart cities, agriculture, energy, technology, healthcare, and other security concerns. Safety concerns currently limit the development of this advanced technology. On the other hand, traditional security protocols and existing solutions cannot be used for IoT because most of them cannot guarantee good performance. Furthermore, they are often severely limited in terms of storage, computing power, and performance. The aim of the proposed research is to introduce a secure verification framework for user authentication, with a special focus on the communication between access points and node databases. The main goal is to increase the level of security within the proposed approach, ensuring the confidentiality, integrity, and availability of the image verification system during the authentication process. To achieve this goal, three phases were implemented. First, a new hybrid biometric pattern is proposed that merges image and password features to enhance the security of user authentication. Second, lightweight Encryption and Blockchain technologies are also utilized to ensure secure communication of patterns between the access point and the node database. Finally, in order to verify authenticity, a new proposed matching process involves comparing image and password features with the database records. The experimental analysis has been carried out in terms of accuracy, False Rejection Rate (FRR), False Acceptance Rate (FAR), and error rate. The proposed approach attained an accuracy of 98%, FAR of 0.1, FRR of 0.992, and an error rate of 0.017.

Survey on Integration of Consensus Mechanisms in IoT-based Blockchains

Article

Full-text available

Oct 2023
J UNIVERS COMPUT SCI

While IoT systems are increasingly present in different areas of society, ensuring their data’s privacy, security, and inviolability becomes paramount. In this direction, Blockchain has been used to protect the security and immutability of data generated by IoT devices and sensors. At the heart of Blockchain solutions, consensus algorithms are crucial in ensuring the security of creating and writing data in new blocks. Choosing which consensus algorithms to utilise is critical because of a fundamental tradeoff between their security strength and response time. However, recent surveys of consensus mechanisms for IoT-based Blockchain focused on individually using and analysing these algorithms. Investigating the integration between these algorithms to address IoT-specific requirements better is a promising approach. In this context, this paper presents a literature review that explains and discusses consensus algorithms in IoT environments and their combinations. The review analyses eight dimensions that help understand existing proposals: ease of integration, scalability, latency, throughput, power consumption, configuration issues, integrated algorithms, and adversary tolerance. The final analysis also suggests and discusses open challenges in integrating multiple consensus algorithms considering the particularities of IoT systems.

Data secure application: an application that allows developers to store user data securely using blockchain and IPFS

Article

Full-text available

Oct 2023
MULTIMED TOOLS APPL

Due to the COVID-19 pandemic, the use of software applications has increased by end users, which is an issue regarding user data privacy. Numerous apps are collecting sensitive data like user location and phone number, which are becoming hotspots for cyber-attacks. A cyberattack breaches your data, attacking your information, thereby losing data integrity, confidentiality, and availability. Cyberattack refers to the unauthorized intrusion of external personnel into a user’s private digital space. We have proposed a solution to provide secure data storage in third-party applications and leverage the power of Blockchain and Interplanetary File Systems. The proposed approach offers reliable role-based access to control data storage service that maintains data integrity, availability, and confidentiality. The proposed model uses the aforementioned technologies because they provide a distributed and decentralized nature of data storage and add-on support to data immutability. Traditionally the technologies used for such services are centralized and provide a single point of attack for the attacker. It puts confidential user data in jeopardy. The proposed solutions store encrypted data distributed to reduce reliance on big tech giants for data storage support and uproot the fear of collapsing systems due to a single point of failure.

Blockchain technology applications in waste management: Overview, challenges and opportunities

Article

Full-text available

Aug 2023
J CLEAN PROD

Rapid population growth and urbanisation have accelerated waste generation, and effective waste management has become a major challenge worldwide. With advances in technology and management methods, waste management strategies have begun embracing digitalisation, leveraging the Internet of Things (IoT), big data analytics, cloud/edge computing, machine learning, 5G communication, and blockchain technologies. Amongst them, the blockchain technology has the structural features of achieving information security and integrity without central guarantees. Blockchain also meets the data record/storage needs of waste management and the design of new mechanisms for effective waste management. These benefits make blockchain an attractive technology in the field of waste management, with researchers and practitioners alike investigating its broad applications to support sustainable waste management. However, this emerging technology has not yet been widely accepted by potential users. To further champion the application of blockchain technology, this review paper provides a systematic overview of the various pathways in which the technology has been applied in the waste management industry and further discusses its related challenges and opportunities via considering the promising prospect of combining blockchain technology with IoT, artificial intelligence (AI) and life cycle assessment (LCA). This review also provides insights for interpreting some emerging applications of blockchain in the field of waste management and clarifying the research paths in the context of blockchain, digitalised waste management, and circular economy.

Fortifying the Blockchain: A Systematic Review and Classification of Post-Quantum Consensus Solutions for Enhanced Security and Resilience

Article

Full-text available

Jan 2023

The inherent security and computational demands of classical consensus protocols are often presumed impervious to various forms of attack. However, quantum computing advancements present considerable threats to the assumed attack resistance of classical security strategies currently deployed within blockchain systems. Adopting consensus algorithms fortified with post-quantum security measures holds the potential to significantly enhance the privacy and security dimensions of traditional blockchains. Notable advantages of such post-quantum solutions in the context of blockchain consensus include accelerated transaction verification, clarified mining authorship, and resilience against quantum attacks. Yet, a comprehensive analysis of the implications of post-quantum solutions for blockchain consensus is notably absent in the existing scholarly discourse. This paper aims to bridge this gap by delivering a systematic review of Post-Quantum Blockchain Consensus (PQBC). The four primary contributions of this study are (i) a systematic approach to presenting a comprehensive overview of PQBC, (ii) the systematic selection and analysis of 29 key studies from an initial pool of 1192 papers, (iii) a critical review of methods, enhancements to security, scalability, trust, and privacy, as well as the evaluation employed for PQBC, and (iv) a discussion of primary gaps and prospective directions for future PQBC research.

Building a Secure Platform for Digital Governance Interoperability and Data Exchange Using Blockchain and Deep Learning-Based Frameworks

Article

Full-text available

Jul 2023

A secured platform is a critical component of digital governance, as it helps to ensure the privacy, security, and reliability of the electronic platforms and systems used to manage and deliver public services. Interoperability and data exchange are essential for digital governance, as they enable different government agencies and departments to share data, information, and resources seamlessly, regardless of the platforms and technologies they use. In this paper, we build a secure platform to enhance the trustworthiness of digital governance interoperability and data exchange using blockchain and deep learning-based frameworks. Initially, an optimal blockchain leveraging approach is designed using the bonobo optimization algorithm to authenticate data generated from smart city environments. Furthermore, we introduce the integration of a lightweight Feistel structure with optimal operations to enhance privacy preservation. This integration provides two levels of security and ensures interoperability and double-secured data exchange in digital governance systems. In addition, we utilize a deep reinforcement learning (DRL) model to detect and prevent intrusions such as fraud/corruption in the smart city data. This approach enhances transparency and accountability in accessing the data and shows its predominance over other cutting-edge techniques on two benchmark datasets, BoT-IoT and ToN-IoT. Furthermore, the effectiveness of the framework in real-time scenarios has been demonstrated through two case studies. Overall, our proposed framework provides a trustworthy platform for digital governance, interoperability, and data exchange, addressing the challenges of privacy, security, and reliability in managing and delivering public services.

A critical literature review of security and privacy in smart home healthcare schemes adopting IoT & blockchain: Problems, Challenges and Solutions

Article

Dec 2023

A review of IoT security and privacy using decentralized blockchain techniques

Article

Nov 2023

BIFData: A Secure Data Trading Marketplace Platform Based on Blockchain Technology and Smart Contracts

Chapter

Jul 2023

The big data industry is rapidly expanding and the data generated by all kinds of devices is increasingly valuable. However, traditional data markets suffer from data silos and lack effective data security mechanisms, which can easily lead to data theft and misuse. With the emergence of blockchain technology, a solution arises. Blockchain is a decentralized, distributed database that records all transactions occurring in a peer-to-peer network. Its unique characteristics can make data marketplaces more secure and transparent. This paper proposes and implements a data marketplace trading platform that combines blockchain and smart contracts. The platform reduces storage costs by storing metadata on the blockchain, manages data providers using a point system combined with federated learning, and improves the system’s operation and storage capacity by using different servers as blockchain nodes. Our implementation is based on the Ethereum platform, and smart contracts are written using the Solidity language. Experimental results confirm the performance of the proposed data trading marketplace platform regarding the security and stability of data transactions.KeywordsData marketplaceBlockchainSmart contractsFederated learning

Hedera: A Permissionless and Scalable Hybrid Blockchain Consensus Algorithm in Multi-Access Edge Computing for IoT

Article

Jun 2023

Multi-access edge computing network (MEC), as one of the key infrastructures of IoT, provides cloud computing capabilities at the edge of radio access network (RAN) by integrating telecommunication and IT services. Integrating blockchain into the MEC network can provide users with secure, private, and traceable edge computing services at the near end, thereby improving IoT security, privacy, and automated use of resources. Due to some characteristics of the MEC network, there are still some challenges to integrate blockchain and edge computing into one system, especially the consensus algorithm of blockchain. The resources of edge computing nodes are limited, and the scale of the network is constantly expanding. Therefore, the blockchain consensus algorithm for the MEC network should occupy as little computing resources as possible, be green, and be permissionless. This paper proposes a permissionless and scalable consensus algorithm "Hedera" for multi-access edge computing network, which has the advantages of permissionless, security, decentralization, scalability, and greenness. The Hedera consensus algorithm is a hybrid blockchain consensus algorithm that combines the permissionless proof-of-capacity algorithm and the permissioned asynchronous Byzantine algorithm. This paper tests the fairness, throughput, scalability, latency, and resource consumption of the algorithm by developing and deploying a prototype system. The experimental results show that the Hedera algorithm proposed in this paper is fair, the throughput reaches 13986.3TPS, and the resource consumption is much lower than the PoW consensus. By analyzing its security and liveness, it can resist Sybil attack, Nothing-at-stake attack, selfish mining attack, message hijacking attack, and has good liveness. Index Terms-IoT, multi-access edge computing, blockchain, hybrid consensus, proof of capacity, asynchronous Byzantine.

Exploring the Potential of Blockchain Technology in an IoT-Enabled Environment: A Review

Abstract

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