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An Overview on Blockchain for Smartphones: State-of-the-Art, Consensus, Implementation, Challenges and Future Trends

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The blockchain technology is currently penetrating different areas of the modern Information and Communications Technology community. Most of the devices involved in blockchain-related processes are specially designed targeting only the mining aspect, i.e., solving the computational puzzle task. At the same time, the use of wearable and mobile devices may also become a part of eCommerce blockchain operation, especially during the on-charge time. The paper considers the possibility of using a large number of constrained devices to support the operation of the blockchain with a low impact on battery consumption. The utilization of such devices is expected to improve the system efficiency as well as to attract a more substantial number of users. This paper contributes to the body of knowledge with a survey of the main applications of blockchain for smartphones along with existing mobile blockchain projects. It also proposes a novel consensus protocol based on a combination of Proof-of-Work (PoW), Proof-of-Activity (PoA), and Proof-of-Stake (PoS) algorithms for efficient and on-the-fly utilization on resource-constrained devices. The system was deployed in a worldwide testnet with more than two thousand smartphones and compared with other projects from the user-experienced metrics perspective. The results prove that the utilization of PoA systems on a smartphone does not significantly affect the lifetime of the smartphone battery while existing methods based on PoW have a tremendous negative impact. Finally, the main open challenges and future investigation directions are outlined.
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Received May 4, 2020, accepted May 26, 2020, date of publication June 1, 2020, date of current version June 15, 2020.
Digital Object Identifier 10.1109/ACCESS.2020.2998951
An Overview on Blockchain for Smartphones:
State-of-the-Art, Consensus, Implementation,
Challenges and Future Trends
1Tampere University, FI-33720 Tampere, Finland
2Enecuum HK Limited, Hong Kong
3ITMO University, Saint Petersburg 197101, Russia
4Brno University of Technology, 616 00 Brno, Czech Republic
5National Research University Higher School of Economics, Moscow 119049, Russia
Corresponding author: Aleksandr Ometov (
This work was supported in part by the Technology Agency of the Czech Republic (TACR) under Grant TJ02000332, in part by the
European Union’s Horizon 2020 Research and Innovation Programme through the Marie Sklodowska Curie Grant through Project
A-WEAR under Grant 813278, and in part by the Government of the Russian Federation, under Grant 08-08.
ABSTRACT The blockchain technology is currently penetrating different areas of the modern Information
and Communications Technology community. Most of the devices involved in blockchain-related processes
are specially designed targeting only the mining aspect, i.e., solving the computational puzzle task. At the
same time, the use of wearable and mobile devices may also become a part of eCommerce blockchain
operation, especially during the on-charge time. The paper considers the possibility of using a large number
of constrained devices to support the operation of the blockchain with a low impact on battery consumption.
The utilization of such devices is expected to improve the system efficiency as well as to attract a more
substantial number of users. This paper contributes to the body of knowledge with a survey of the main
applications of blockchain for smartphones along with existing mobile blockchain projects. It also proposes
a novel consensus protocol based on a combination of Proof-of-Work (PoW), Proof-of-Activity (PoA), and
Proof-of-Stake (PoS) algorithms for efficient and on-the-fly utilization on resource-constrained devices. The
system was deployed in a worldwide testnet with more than two thousand smartphones and compared with
other projects from the user-experienced metrics perspective. The results prove that the utilization of PoA
systems on a smartphone does not significantly affect the lifetime of the smartphone battery while existing
methods based on PoW have a tremendous negative impact. Finally, the main open challenges and future
investigation directions are outlined.
INDEX TERMS Communication system security, cryptographic protocols, distributed information systems,
mobile computing, prototypes, cellular phones.
Today, the number of mobile devices is growing tremen-
dously. According to CISCO, there were more than 0.7 billion
wearable devices in 2017, with almost 44% being smart-
phones [1]. This number is expected to reach 12.3 billion
mobile-connected devices by 2022, which will exceed the
world’s projected population at that time (8 billion) by one
The associate editor coordinating the review of this manuscript and
approving it for publication was Patrick Hung.
and a half times. This rapid growth is largely forming a
standalone niche of Internet of Wearable Things (IoWT) [2]
as part of the enormous Internet of Things (IoT) paradigm [3].
The mobile devices present on the market today already
have the computational power of 5 years old computer [4],
allowing for broader utilization of those not only for calls
and human-based data exchange but also for much more
complex computational tasks opening a broad way for various
emerging applications [5]. One of those tasks is related to
the operation of the distributed solutions, as part of future
103994 This work is licensed under a Creative Commons Attribution 4.0 License. For more information, see VOLUME 8, 2020
A. Ometov et al.: Overview on Blockchain for Smartphones
Cyber-Physical Systems (CPS), relying on blockchain tech-
nology, which is expected to affect the society at large
by storm.
Historically, blockchain systems known today are made
on the basis of the system proposed by Ralph C. Merkle in
1979 [6]. In recent times, the applications that could previ-
ously work only through trusted centralized entities achieved
an opportunity to operate without any constant connection to
the authority while maintaining the same security level and
improving the overall system functionality [7]. The main idea
behind blockchain itself lies in the concept of trust [8], [9].
This idea is based on the fact that parties interacting within
the system do not necessarily know or trust each other but still
have an opportunity to transact securely. By these means, the
use of blockchain eliminates the need for the involvement and
continuous maintenance by the centralized ‘trusted’ author-
ity, thus, enabling the network to operate in a completely
distributed manner.
At the same time, the possibility to customize and style
along with technological enhancements towards small-scale
electronics and modern applications make handheld and
wearable devices a strong contender in the IoT technological
race [10]. This fascinating development is a driving force
behind the convergence of the physical and digital worlds
that promises to create an unprecedented IoT market of
$52 billion during the oncoming years [11]. Moreover, it is
expected that a significant percentage of those devices will
be smartphones, tablets, and wearables. Currently, there are
about 3.2 billion smartphones in the world [12], and the
average one can process 2 billion floating-point operations
per second (FLOPS) [13], thus, leaving us with constantly
underused 5 EFLOPS. If needed, this power can be applied
for the transaction publication and validation processes, smart
contracts [14], incentivization by cellular operators [15],
trusted data crowdsensing [16], or distributed storage [17].
However, deploying blockchain applications to mobile
and resource-constrained devices acting as actual miners,
i.e., nodes solving a highly-complex computational puz-
zle or Proof-of-Work (PoW), faces many critical chal-
lenges [18], [19]. The PoW mining process habits requires
not only computing power but also energy from interacting
mobile devices. There are, however, several miner implemen-
tations of blockchain applications for smartphones, but it has
been shown that the income of a single mobile device acting
as a miner in the blockchain network is nonprofitable [20].
It is worth pointing out, the use of constrained devices is
generally underestimated in the context of blockchain. The
mining feature is ultimately not the most efficient utilization
of this class due to the computational and power limitations,
but the concept known as Proof-of-Stake (PoS) provided the
first opportunity for such constrained devices utilization [21].
Here, PoS nodes do not act as miners to solve complex tasks
but rather as temporary authorities [22] to confirm transac-
tions and blocks based on their ‘‘stake’’ in the system, and
the use of the resource-constrained device, for this reason,
is a natural step forward. The role of PoSs is to pay only
the transaction fees of the network without involvement in
actual mining.
Nonetheless, almost every modern smartphone already has
the power to act the part of not computationally hungry
Proof-of-Activity (PoA) operation [23] and calculate related
cryptographic primitives [24]. Broadly, PoA aims at validat-
ing the transaction instead of signing or mining the blocks.
To throw some oil on the fire, vendors are already providing
blockchain-enabled smartphones for public use, foreseeing
the inevitable future of distributed applications on handheld
devices. Some devices already have native support for decen-
tralized applications, including, as of May 2020, Samsung
Galaxy S10, HTC Exodus, Sirin Labs Finney, Pundi Xphone,
and Electroneum M1.
Based on the above, the evolution of blockchain towards
mobile electronics in the state of the technology nature.
Therefore, this paper aims to (1) analyze the state-of-the-art
in mobile blockchain systems and (2) to propose a hybrid con-
sensus protocol with low impact on smartphone operation.
The main contributions of this work1are:
Overview of existing trends in blockchain applica-
tions related to resource-constrained and wearable
devices. Goal 1
Comparison of existing ‘living’ projects involved in
smartphones-based blockchain processes. Goal 1
Development of a protocols’ family and its implemen-
tation allowing for efficient blockchain integration on
modern smartphones and its security analysis. Goal 2
Performance evaluation of publicly available
smartphone-based blockchain solutions along with the
developed one and the corresponding impact on the user
experience of the device owner. Goals 1 and 2
Outline of the main challenges and future perspec-
tives of the blockchain adoption by both users and
industry. Goal 1
This survey summarizes recent industrial activities and
research breakthroughs on blockchain and blockchain-based
applications and open challenges for smartphones and
resource-constrained devices. In order to identify key pub-
lications on the analysis of the blockchain technology, a liter-
ature search in scientific databases was performed covering
leading computer science journals and conferences: IEEE
Xplore,ACM Digital Library,ScienceDirect,SAGE Journals
Online, and Springer Link. To find relevant articles and papers
for our research, the following search string was compiled and
used: (Blockchain OR ‘‘Distributed Ledger’’) AND (‘‘State-
of-the-Art’’ OR Challenges OR ‘‘Performance Evaluation’
OR Attack OR Implementation OR Prototype OR ‘‘White
Paper’’). Industrial blogs and project White Papers were also
analyzed, covering the present phase of technology devel-
opment and integration. In total, a set of 1312 potentially
1This paper is a significantly extended version of published work [25].
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A. Ometov et al.: Overview on Blockchain for Smartphones
relevant publications was completed, excluding grey litera-
ture and pre-prints.
During the reviewing process, the titles, keywords, and
abstracts of the publications were analyzed to identify papers
and articles that were relevant to the problematics of the
blockchain applications for mobile devices. As a result, a total
of 60 publications were selected. To further extend the liter-
ature sample, a more in-depth analysis of the selected publi-
cations references was executed, aiming at additional papers
or articles relevant to the research action. Accordingly, this
process resulted in a total of 79 publications.
Once the literature selection process was completed, the
selected publications were carefully read, and an open coding
approach was applied to identify the described applications
and challenges. Next, the extracted applications were classi-
fied into four general groups. The results of the analysis are
presented in the next section.
The rest of the paper is organized as follows.
In the first place, this paper outlines the main applica-
tions of blockchain technology for smartphones and wear-
able devices stepping aside from conventional cryptocurrency
perspective in Section II. The overview covers such areas
as infrastructure and resource sharing, security and access
control, trust, and user involvement aspects.
Next, the study surveys various market-available
blockchain-based systems and related consensus algorithms
in Section III. It elaborates on the actual involvement of
resource-constrained devices in the blockchain ecosystem
Based on the analysis, this paper contributes with a hybrid
algorithm, coupling together Proof-of-Work, Proof-of-Stake,
and Proof-of-Activity, which allows involving mobile devices
in the new block generation process, as detailed in
Sections IV. Section Vprovides a detailed description of the
developed cryptographic protocols.
Section VI provides the performance evaluation of existing
solutions from Section III and the developed system as well
as its qualitative security and privacy analysis.
Section VII sheds some light on several open challenges
that should be considered by the blockchain system devel-
opers. Finally, this section highlights future perspectives of
the utilization of blockchain on smartphones. The last section
concludes the paper and summarizes the main findings.
Despite conventional applications such as cryptocur-
rency [26], governance, Distributed Ledger Technol-
ogy (DLT) operation [27], and supply management [28],
smartphones and resource-constrained wearables are natu-
rally involved in a plethora of networking activities driven
both by humans and devices themselves. This section outlines
the applications mostly related to smartphones and other
resource-constrained devices.
One of the constantly evolving markets of today is related
to cellular communications driven by the 3rd Generation
Partnership Project (3GPP) organization actively develop-
ing Long Term Evolution (LTE)-related standards. The
number of directions for the application of blockchain in
LTE is vast and accomplished with Wireless Local Area
Network (WLAN) services, broadly deployed worldwide.
Moreover, the Federal Communications Commission (FCC)
shared tentative thoughts to deploy blockchain as an enabler
for 6G in 2018 Mobile World Congress (MWC) [29].
Today, both vendors and operators have access only to
limited resources from energy, computing, and spectrum per-
spectives [30]. From the operator’s point of view, the radio
resource is the biggest bottleneck due to the growing demand
for various applications, including Virtual and Augmented
Reality (VR/AR) applications, high definition video stream-
ing, and Tactile Internet paradigm [31]. Spatial and spectral
resources of different operators may be unequally used due to
various reasons and, thus, such systems as Licensed Shared
Access (LSA) [32] and Licensed Assisted Access (LAA) [33]
were proposed by 3GPP. Blockchain technology may
become one of the enablers for making the manipulation
with those resources more flexible, especially in the IoT
context [34].
In particular, the work [35] proposes the adoption of
blockchain technology as a virtualized intermediary for the
shared use of network resources in a sovereign, autonomous,
safe, and reliable mode. The authors highlight the possi-
bilities of the infrastructure and network resources sharing
through Peer-to-Peer (P2P) self-executing transactions in a
distributed manner.
The authors of [36] also focus more on the Network Func-
tions Virtualization (NFV) in 5th generation networks (5G). In
particular, this work proposes to utilize blockchain for intelli-
gent network slicing in Software-defined Network (SDN) by
introducing Blockchain Slice Leasing Ledger Concept for a
5G network. Here, the mobile network service provider has
the ability to compromise with external tenants’ network slice
requests quickly and automatically relying on the accessibil-
ity of infrastructure provider resources.
The topic of content-centric data sharing form privacy
perspective is discussed in work [37]. The authors propose
to combine blockchain and encrypted cloud storage in a
content-oriented network in order to maintain the users’ con-
fidentiality and secure data exchange flexibly. The authors
of [38] facilitate the use of blockchain for incentivization in
terms of distributed data storage. The data stored by each
node is considered to be a block in the chain. The reward
will be received by the node that stored the data, and the
reward for the sale of the node increases with the volume
growth of stored data. The study in [39] provides a pro-
found overview of the Cloud Exchange (CloudEX) storage
empowered by blockchain technology aiming to avoid the
additional need for an intermediary and empowering trust at
the same time.
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The potential of offloading the resource-intensive mining
tasks to neighboring computing nodes with blockchain is
discussed in [40] concerning data caching. The paper ana-
lyzes the computational offloading and content caching in
wireless blockchains with Mobile Edge Computing (MEC).
The authors focus on the offloading strategies selection, i.e.,
offloading to the nearest Access Point (AP) or a group of
users in device-to-device (D2D) proximity, and the caching
strategy regardless of whether to cache the requested content
and computing or not. Those approaches are jointly studied
and formulated. The study [41] describes a similar edge com-
puting problem, and the work [42] focuses on Cloud and Fog
operation aspects. The authors of [43] also propose the secure
data sharing framework based on blockchain in combination
with D2D applicable for Delegated PoS operation. The results
have shown that the use of an AP-based relaying strategy may
significantly improve the utility of Edge nodes by means of
computational offloading while mobile devices were acting
as PoS nodes.
Another large segment of blockchain applications on mobile
smartphones is related to access procedures and tracking from
different perspectives.
The works [44] and [45] highlight accessing the Internet
via blockchain-powered access control, which allows keeping
records of transactions that track the device actions (access
nodes, channels, gateways, services, etc.). It allows for flexi-
ble economic compensation for used resources in a transpar-
ent, decentralized, and reliable way. The authors of [46] also
puropose a protocol to apply blockchain for access manage-
ment in public Wi-Fi APs. The method is based on virtual
credentials instead of actual user information.
The authors of [47] develop and implement an authentica-
tion scheme to concurrently and efficiently ensure anonymity
and accountability without dependence on any trusted third
party. The system uses the unmodified Bitcoin blockchain as
a platform for managing and determining access credentials
in a peer-to-peer way. The method suggests associating the
user’s access right with their bitcoin address, which can be
used as credentials to access public Wi-Fi APs.
Another work [48] proposes a blockchain-based cross-
domain authentication scheme for Wi-Fi networks. The
designed solution authenticates users and servers in a dis-
tributed and anonymous way, avoiding a single point of fail-
ure and privacy leakage.
The identity management aspect is also in the focus of
the study [49]. The authors suggest a privacy-enhancing user
identity management system based on blockchain technology
that gives due importance to both anonymity and attribution
and also supports end-to-end management from user approval
to billing for use. The setting provides access to the network
using aliases, preventing the restoration of subscriber identity.
An exciting niche of the blockchain application falls in
the area of Self-Sovereign Identity (SSI) [50], [51]. With the
term not being fully defined, it generally corresponds to an
identity management system allowing individuals to own and
manage their digital identity fully. From a broad adoption per-
spective, there is a very active scene creating ‘‘wallet apps’’
for storing Verifiable Credentials (VCs) and Decentralized
Identifiers (DIDs). An example or a real-life implementation
is the application called ‘‘Bloom – Secure Identity’’ providing
a protocol for SSI on modern smartphones [52].
The authors of [53] propose to utilize private blockchain
for detecting malicious applications in application stores. The
idea behind is to enable third parties to execute independence
security scans of the application after it is published and add
the result to the chain aiming to decrease the false positive
rate of detection systems.
In the medical domain, the research work [54] proposes
to apply blockchain technology for the insider attack mit-
igation in the Internet of Medical Things (IoMT). The
authors focused on Medical Smartphone Network (MSN)
environment and developed a trust management scheme. The
proposed approach allows the users to quickly update the
blacklist of nodes to analyze the information about the status
of traffic from suspicious ones better.
The decentralized trust management scheme based on the
blockchain technology is proposed in [55]. It enables mobile
nodes to evaluate the trustworthiness of neighbors based
on the Bayesian Inference Model and assess the credibility
of received messages. Another trust management scheme is
proposed in [56], where the authors have introduced a token-
sharing scheme that motivates users to share information
The authors of [57] focus on the aspects of trust in Wireless
Sensor Networks (WSNs). This article proposes a new appli-
cation for the blockchain as a secure decentralized storage
for cryptographic keys, as well as for exchanging of trust
information in the context of autonomous wireless sensor
networks. The proposed mechanisms depict how to apply
the blockchain immutability to solve problems in the field of
decentralized ad-hoc networks, i.e., how to build a complete
solution that provides authentication mechanisms as well as
an assessment of trust in a self-organizing network.
In contrast to many anonymization-targeted works,
paper [58] proposes the system that aims to map personnel
information to the blockchain-based transaction system by
creating digital identities based on identifiers issued by the
government. This digital identifier is associated with a mobile
device. The system is based on the biometric parameters
and trust computing technology to ensure that the infor-
mation stored in the blockchain correctly reflects reality.
The work [59] also provides an overview of the blockchain
potential from a biometrics perspective.
Blockchain could also be used for data crowdsourcing, as
it is examined in [60]. This work aims to preserve the privacy
of the participants and keep the integrity of the service request
and provision. The authors of [61] also propose to utilize
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A. Ometov et al.: Overview on Blockchain for Smartphones
the blockchain to avoid third party involvement during the
crowdsourcing process.
Since the roots of publicly-known blockchain technology lie
in the financial field, some researchers propose to utilize
blockchain as a user incentivization mechanism, which was
already discussed in [56], [62], [63]. Interestingly, the authors
of [64] propose a blockchain-based incentivization schema
for Public Protection and Disaster Relief (PPDR) scenarios.
The approach uses a smartphone with a delay-tolerant net-
work (DTN) support, which relies on Bitcoin to encourage
nodes to collaborate. The scheme is entirely decentralized and
independent of any central trusted authority.
Another standalone niche based on the cryptocurrency
concept is related to online- and P2P based gaming [65], [66].
The application of blockchain for both in-game cryptocur-
rencies and/or centralization of gaming events would allow
creating a secure and fully decentralized architecture to
transform a game towards becoming community-sustainable.
It is foreseen that blockchain would bring completely new
paradigms to the gaming industry, including more excit-
ing and parallel gaming universes, better-regulated gaming
economies, faster micro-transactions, fraud resistance, and
general fairness to players [67]. Overall, blockchain-based
gaming already benefits from the features of decentralized
applications (DApps) [68].
Generally, the blockchain potential in applying it to com-
munications and related aspects as a specific niche is still
in its infancy. Most of the presently developed solutions
for smartphone-related scenarios focus on resource sharing,
access control, user involvement, and incentivization. The
main driver behind the broad adoption of blockchain in the
wireless environment would still be hardware providers and
operators due to their tight connection to mobile devices
Indeed, the blockchain development towards smartphones is
still in the infancy. On the other hand, there are some ongoing
public projects actively working in this direction. This section
highlights the main concepts and related paradigms in the
current mobile blockchain area.
Due to the blockchain property of immutability, it can be
abstracted as a transactional system that enables a consensus
to form within its participants [69]. The consensus holds
unique probabilistic properties and can thus be leveraged as
a fundamental building block for adaptive middleware that
offers both deterministic and probabilistic consensus.
Most of the public blockchain operation known today is
based on specially designed devices – miners, i.e., nodes that
attempt to solve the computational puzzles, in other words, to
achieve the PoW [70], [71] for new block creation, and profit
from the monetary compensation associated with it. The first
node to solve the computational puzzle receives a reward.
In order for the system to stay operational, the complexity
adjustment (often known as ‘‘number of leading zeros’’) is
utilized, i.e., in fact, it aims at minimization of the number
of nonces which need to be tried before a match is found.
The difficulty of mining should be adjusted dynamically
throughout the lifetime of the system [72].
This subsection lists living PoW-based blockchain systems
available on smartphones.
The first system is the Mobile SmartX Blockchain platform
based on Mobile Integrated Blockchain (MIB) coin. MIB
public network was launched on November 12, 2018, reach-
ing more than a thousand active users just two weeks after
release [73]. A year after the release, the number of active
users has almost reached two thousand.
MIB is branded as environmentally friendly, inexpensive
PoW mining for mobile devices based on Bitcoin. The main
difference is that MIB’s Mobile Proof-of-Work (MPoW) uti-
lizes the CPU resources of mobile devices to mine blocks.
The application is designed to take into account the capa-
bilities of the device; users can choose the desired min-
ing complexity to protect the smartphone from overheating,
allowing budget devices of any processing power to be part of
the network. Low-power PoW is another MIB feature. MIB
states that the smartphone application spends 150 times less
power than an application-specific integrated circuit (ASIC)
mining [74].
It is essential to point out that the MIB network is cen-
tralized. Network servers assigned by the project owners
distribute cryptographic tasks between nodes, and then they
publish blocks. Thus, mobile devices do not support a dis-
tributed network, but the servers they are connected to. The
control over the network remains with MIB executives. Hav-
ing created a centralized network, the project is deprived of
one of the distinguishing features of blockchain technology,
i.e., a distribution that allows one to send transactions without
a generally trusted third party but a selected one.
To finalize, MIB application is not able to be executed in
the background mode, making every-day use of smartphone
inconvenient. The need to keep the application constantly
open makes MIB mining possible only on spare devices of
specifically designed farms, which makes MIB operation
costly not only from hardware but also from energy consump-
tion perspectives.
2) uPlexa
uPlexa’s main goal is to form a platform for IoT devices
to create an anonymous blockchain-based payment system.
The beta version was released in 2018. At the beginning of
2019, the uPlexa team developed an Android application for
the public domain. As of now, users can also use it on their
PC CPU, Android device CPU, AMD GPU Devices, and
Nvidia devices.
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A. Ometov et al.: Overview on Blockchain for Smartphones
uPlexa also relies on the PoW concept, i.e., IoT devices’
CPU or GPU resources are used to add transaction records
to the ledger. It creates an anonymous payment system with
the support of interlinking IoT devices, which can be used for
telecom and internet service providers for e-commerce.
uPlexa aims at overcoming Bitcoin’s issues, specifically,
slow transaction time and hefty fees, by introducing a model
where micropayment fees increase when the network is over-
loaded. This method helps decrease the amount of these
micropayment transactions and, consequentially, lower the
load on the network. At the same time, in order to sustain
the balance, any other payments still have low fees.
The project allows operation on different types of hard-
ware, including phones, tablets, PCs, TVs, TV Boxes, Rasp-
berry Pi’s, and the team is planning to scale the list by
supporting as many IoT devices as possible while keeping
the mining ASIC-resistant.
Since IoT devices vary significantly, the uPlexa application
offers a choice between different settings to fit each device’s
resources. So, the users can adjust the level of CPU usage and
the number of threads to be utilized to prevent over-use and
Smartphone-based blockchain applications may rely not only
on computational resources but also on transporting the value
between involved instances. Here, devices are competing on
accumulating transactions to generate new blocks and get
transaction fees. An example of this activity is a TAU Coin,
which Android application was released in May 2019, though
its users were active since 2018. Currently, there are more
than 440,000 registered accounts but less than a thousand
active ones as of May 2020.
The project’s algorithm, Proof-of-Transaction (PoT),
determines a new block generation address based on accu-
mulated transaction history [75]. For every address, there
is a linear proportion between the new block generation
probability and the address’ transaction history, and this pro-
portion is called mining power, which is an equivalent to
Bitcoin’s hash power. The more transactions the user has
made, the higher the chance of receiving rewards, which come
in the form of a transaction fee. The algorithm incentivizes
users to make transactions actively and thus increase coin’s
Unlike other projects that use PoW and PoS algorithms,
TAU has its entire coin supply already minted in the gen-
esis block. The reason for that is to fight the hoarding
(stockpiling) mentality that is present in the cryptocurrency
market. The platform rewards active participants of the net-
work who make transactions and the currency circulates
TAU has security measures against the majority or 51%
attack; the attacker would need to have more transactions than
the rest of the network combined for a year, which makes the
attack highly challenging to perform.
Cloud mining, a process of token mining using a remote
datacenter, is a new concept that is utilized in Electroneum
and Phoneum projects. Cloud mining is provided for free and
delivers an easily understandable experience, allowing users
to participate regardless of their hardware and knowledge of
cryptocurrency economy and mining algorithms.
Electroneum is one of the most popular smartphone-based
mining projects [76]. Following the start of the development
in 2017, Electroneum held a successful ICO sale, and by the
beginning of 2018, the beta version on an Android application
was launched. By Q3 2018, the project reached two million
registered users. As of May 2020, there are around 2.5 million
registered users and 200,000 active miners.
Electroneum is resistant to 51% attack; the security is
achieved by the addition of a moderation layer, which
becomes active when there is a possibility of an attack. The
layer establishes the attack’s origin and shuts it down.
Electroneum is compliant with a Know Your Cus-
tomer (KYC) process; the platform requires users to fill out
their legal name and surname, country, telephone number, and
upload their photo to verify their identity and to minimize the
risk of illegal use of the app. This, however, may compromise
the user’s privacy, since the entered information is shared with
third parties according to the project’s policy.
Phoneum is another project that utilizes cloud mining [77].
After almost two years of development, the Phoneum mining
application, as well as a gamified platform, had been released
in May 2019.
The project is designed to function on multiple platforms
and has been implemented in a gamified experience as a game
called Crypto Treasures, where users can earn Phoneum’s
currency by playing games. The project is expected to have
an easy to integrate API to allow other developers to utilize
cryptocurrency in their projects.
Cloud mining utilized in both Electroneum and Phoneum
is activated through the corresponding applications without
any prerequisites and requires reactivation every week. The
rewards are distributed for free once mining is started. The
smartphones, however, do not perform any activity and do
not help confirm new blocks, and as a result, they do not
bring blockchain utility. Since the apps and the cloud mining
services are free and do not require an entry fee, it makes the
rewards easy to gain and, eventually, decreases token’s value.
Based on the analysis of the existing projects, the major-
ity of those were found either relying on computationally
expensive mechanisms or not involved in block generation at
all, which may result in the need to pregenerated the blocks
anyway, i.e., to have the empty blocks already prepared for
utilization. In the next section, we propose our approach that
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FIGURE 1. Smartphones as part of the blockchain ecosystem.
may be potentially used for mobile blockchain operation and
compare it with the listed solutions.
This section provides a brief overview of the main system
components used during protocols development.
An intelligent combination of PoA, PoS, and PoW is
proposed aiming at the involvement of mobile devices for
blockchain operation (see Fig. 1). As a baseline, the system
utilizes ID-based cryptography initially discussed in [78]
during the times when blockchain itself was brought to the
research community’s attention. After 20 years, the first
realization of this strategy took place in work [79] by
C. Cocks et al. They proposed a new approach of obtain-
ing the sender’s secret key to generate a signed message
using a private key generator (PKG) and a unique sender ID.
However, there are several challenges related to PKG utiliza-
tion: (i) PKG can sign and decrypt all the messages; (ii) key
revoking is not implemented; (iii) safe channel is required
for the key dissemination; and (iv) encryption and decryp-
tion mechanisms are computationally different. Most of
those could be mitigated by utilizing Shamir Secret Shar-
ing (SSS) [80], allowing for the PKG secret key dissemination
and reconstruction based on only a portion of previously
distributed shares, which is used in the developed algorithm.
In particular, a hybrid multi-level architecture is proposed to
achieve better fairness and flexibility of the system operation.
Here, the first level consists of a large number of devices
with limited computing and communication capabilities (i.e.,
PoAs), while the second level devices have significantly
greater capabilities (i.e., PoSs), carries greater responsibility
and greater risks for the functioning of the system due to
distributed decision making. The third level consists of the
devices responsible for solving the computational puzzle (i.e.,
PoWs). The involvementof the devices from all three levels is
required in order to add a new block to the blockchain, which
is detailed further in this section.
The system defines four types of major components
that would be explained before proceeding to the actual
operation (see Fig. 2):
FIGURE 2. Proposed block structure.
1) k-block – is the actual block added to the blockchain,
which is a result of a computation puzzle solution by
PoW, which is based on macroblock signed by a trusted
PoS node with high stake along with a group of PoAs
acting as verifiers. The generation of k-block requires
significant computing and energy resources, as well as
an online presence.
2) Macroblock – is a temporary block signed by currently
selected Leading PoS node.2Its header is generated
prior to sending it to a group of PoA nodes for actual
transaction verification (via microblocks, see the next
item). After the verification phase is complete, the
LPoS signs a set of verified microblocks (macroblock)
and broadcasts it to PoW nodes for adding to the
blockchain. Macroblock generation requires a signif-
icant stake of tokens and the online presence of the
current LPoS node.
3) Microblock – is a set of transactions signed by cur-
rently selected LPoS node and verified by a single
PoA node together with the macroblock header. Not
a computationally hungry task and does not require
constant online presence – PoA may participate in the
2The Leading PoS (LPoS) is one of PoS nodes selected by pseudorandom
procedure or the voting of other PoS nodes, i.e., a portion of PoS nodes should
approve the announced potential LPoS to take its role for this block.
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verification process voluntarily since the number of
PoA nodes is typically high.
4) Transaction – the peculiar data to be added to the
blockchain. It is originated from nodes outside the con-
sensus. It may contain certain rules or smart contract-
related information (encrypted to assure the data pri-
vacy if required).
Overall, k-block is the top-level result of the interaction by
all nodes with different roles listed further.
PoS nodes are holding a significant amount of tokens, thus,
becoming a more trustworthy part of the system opera-
tion (similarly to banks and trusted authorities). Any node
can prove the eligibility to become a holder by staking the
highest number of tokens (currently set to 10% of all available
tokens). Key SKHK is a shared key distributed between a set
of holders based on the Lagrange interpolation formula [81].
The corresponding PKHK is known to any node. The resident
node is responsible for SKHK generation, and a group of
holders forms a PKG.
The resident’s functions are: (i) to store SKHK ; (ii) to
distribute it to other PoSs; and (iii) to estimate the Lagrange
polynomial properties. After the resident is stopped, the key
shares will be distributed to PoS according to protocols
described in subsections V-G and V-H. The Lagrange poly-
nomial characteristics would not be possible after the resident
leaves the system and, thus, they should be adjusted after the
initial period of the system operation.
Holders are systematically executing the protocol
described in subsections V-A to verify who has the right to
distribute the publication keys during this system operation
state. The corresponding time interval is set to 100 k-blocks
in the simulation environment. The Leading PoS (LPoS)
selection result is then stored as statistic blocks and may
be verified by any node. Selection is based on the pseudo-
random procedure or the voting of other PoS nodes, i.e., a por-
tion of PoS nodes should approve the announced potential
LPoS to take its role for this block.
Next, the required number of PoSs are involved in the
session secret key for LPoS generation after the k-block
retrieval. The publication public key is calculated based on
the k-block ID (hash sum) and LPoS ID. The secret key and
the corresponding shares are calculated based on the proto-
col described in subsection V-B. The holder gets a reward
for participation in the voting and PKG-related procedures.
Therefore, current LPoS recovers a version of the secret
key from other PoS miners. A session key is required to
sign microblocks. Only LPoS with all necessary key shares
of the secret key can accept and sign blocks from PoA
LPoS announces the possibility to verify current transac-
tions to be added to the block to a set of pseudo-randomly
selected PoA nodes and the ones who replied receive the
transaction(s) signed by the session key to be verified and
further combined into the macroblock, see subsection IV-A2.
After PoAs have successfully verified the transactions, the
macroblock is broadcasted to available PoW nodes, accord-
ing to subsection IV-A3.
PoA nodes are involved in the microblock publication pro-
cess. The main task of the PoA nodes is to listen to the
network continuously. Each PoA in the group of selected
PoAs verifies the signature of the delivered microblock pay-
load (array of transactions) and forwards the signed version
back to the LPoS in case of the verification success. After the
LPoS received all microblocks verified by PoAs, i.e., all data
becomes validated by PoAs and LPoS node in the system,
their participation may be verified later.
Microblocks must be verified and signed by PoA nodes
using their own secret keys. The participation of PoA nodes
is ensured by their binding to the specified k-block. PoAs
are resource-constrained devices and are not involved in the
‘mining’ process. In brief, PoA nodes are limited in terms of
computing and communications and, accordingly, are ded-
icated to the operation on smartphones. PoSs – could be
stationary power- and storage-independent nodes. The num-
ber of PoS nodes is expected to be smaller (by orders of
magnitude) than PoAs’.
PoW nodes are responsible for the generation of new k-blocks
from macroblocks delivered from current LPoS. The main
requirements for this type of nodes are (i) reliable access
to the Internet; (ii) storage (required to store the blockchain
structure); and (iii) computational power for hashing. The
solver is recursively calculating nonces for new k-block gen-
eration according to the set of predefined rules – difficulty,
batch number, hash links validity. Each k-block is distributed
through the network in a broadcast way after its generation
to PoS and, potentially, PoA nodes. Each node checks its
validity based on locally stored data and adds it to local
blockchain storage if valid.
As a baseline, widely known Nakamoto protocol [82] is
used for the blockchain construction. PoW’s main aim is to
generate the block and obtain the resulting award for the com-
putational expenses. The k-block contains its public key. The
selection of the hashing function does not affect the overall
system operation directly. RandomX function, developed by
Monero [83], is currently adopted on the PoW side in order
to increase the fairness of the system.
For example, at the ith time instant of the blockchain opera-
tion, ki1k-block from i1th interval is already present in
the blockchain and new transactions begin to appear. LPoS
is selected by active PoS nodes by advertising itself along
with its stake. PoSs that agreed on LPoS selection (based on
the advertised stake probabilistically), provide it with ‘salted’
secret shares and, if the number of shares is higher than
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FIGURE 3. Proposed system block publishing process.
required by SSS threshold, LPoS constructs the session secret
key used for signing microblocks and current macroblock.
Next, LPoS announces the possibility of verifying the
transactions for future k-block for all online PoAs. A group
of PoAs from the replied ones is selected by LPoS based on
the pseudorandom procedure. If at least one of the selected
PoAs will interrupt the communications during the oncoming
phases – the group of PoAs selection procedure should be
restarted by LPoS.
LPoS then signs each set of transactions with the session
key and sends those to different PoAs from the group. PoAs
verify the signature and sign the own microblocks with a
personal secret key. Finally, each PoA returns the signed
microblock to LPoS, which further combines those in the
Merkle tree and signs by its own secret key.
By this means, a new macroblock is generated based on
the previous k-block from i1th interval, the root hash of
the Merkle tree of the collected and signed microblocks, and
its signature created by LPoS selected during the ith interval.
LPoS is sending the generated macroblock to PoW nodes in
a broadcast way, and the fist PoW to solve the computational
puzzle adds it to the blockchain. Simply, the proposed process
of the block publication is explained in Fig. 3. The following
subsections describe the relationship between the blockchain
The proposed blockchain construction algorithm belongs
to the permissioned category since PoA nodes sign the
microblocks they form with own secret keys, public keys are
known, and all PoS are known, and the procedure for entering
a node into the PoS category is public.
Bitcoin-NG protocol is selected to handle macroblocks [84]
to reduce the latency between the creation of blocks so that
each microblock inside a macroblock is created in real-time
and adds transactions to the blockchain immediately upon
their arrival. So, there is no need to wait until an entire
macroblock is completed, its hash is found, and it is synced
between all nodes in the network – small microblocks can be
generated concurrently inside it. The main reason behind the
utilization of this protocol lies in its possibility to increase
the mining speed in the system, i.e., to increase the number
of blocks generated by the system within the selected time
frame. The fundamental limit here is the distribution time
of the newly generated block between all the nodes in the
system. In case the generation time is shorter, the probability
of forking in two distant sections of the network may arise
tremendously. Direct Acyclic Graph (DAG) [85] allows the
addition of new blocks in different network segments han-
dling the forking.
The goal of DAG is to deterministically rearrange the k-
blocks for the ledger recalculation based on the following set
of requirements:
Graph construction and graph walk procedures are
developed minding the consensus between the nodes,
i.e., there is a need for defining the minimal number of
nodes to guarantee the validity of current system state at
any time of execution;
New k-block is validated (added to consensus) during a
specific time frame;
New k-block should be inserted in the chain according
to its publishing time;
Addition of a new k-block should not require the traver-
sal of the entire graph;
Long-time forks should be avoided.
Generally, PoWs form k-blocks according to the standard
rule, providing the specified properties of the hash, thereby
confirming the work done. The primary purpose of the work
is to streamline the general chain of events. The main draw-
back is that they cannot build blocks too often, while they
cannot provide sufficient transaction transfer speed.
First, the graph walk procedure is defined, starting with
inverting the DAG. Next, the Queue-based topological order
algorithm is applied to the graph as by iterative removing of
the nodes and storing the logs of this process, see [85]. The
system utilizes a deterministic algorithm allowing to calculate
the difficulty for each k-block during the graph traversal.
Therefore, every new k-block is considered valid if its hash
is equal to its difficulty. This algorithm allows to calculate
the value branch_max during the graph traversal based on
the k-block number,brunch (0 <branch <branchmax ).
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Each k-block shas two links to previous and next k-blocks
t1and t2such that t1.branch == s.branch and t1.branch ! =
s.branch despite the case when branchmax =1.
New k-block generation procedure is described as follows.
First k-block has branch =0,number =0. It is valid if:
1) {number,branch}pair is unique;
2) k-block has links to t1and t2,t1.branch == s.branch,
t1.branch ! = s.branch,s.number >t1.number.
In case there are more than one s, the one with higher
t2.number will be accepted;
3) k-block’s hash is equal to difficulty.
The following parameters are considered during the ledger
calculation: k-block mining, a reward for microblock pub-
lishing, and transaction fee. The rewards are dynamic and are
based on the blockchain operation history. The transactions
inside the microblock are stored in a sorted array. Therefore,
all k-blocks, microblocks, and transactions could also be
arranged for any DAG size. As a result, the entire history of
events could be linearly retrieved allowing to calculate the
states of the account balance.
At the beginning of the execution, the ledger is empty. Dur-
ing the block rewarding process, the balance of the existing
account will be changed, or a new record will be found. The
states of nodes are updated during the transactions accord-
ingly. The transaction is treated as invalid if there is no infor-
mation about the account in the ledger, or it has not enough
tokens in the wallet. Invalid transactions are discarded.
The estimation of the reward is based on the deterministic
algorithm for each system state relying on history and the
current block. The estimation of rewards depends on the emis-
sion curve and current emission distribution. Initially, the
distributions are as follows: PoW – 10%; PoS – 25%; and PoA
– 65% of the emission. The emission distribution balance is
a dynamic system property and could be used as a tool to
mitigate malicious activity between different nodes based on
a specifically selected emission curve. Generally, the values
of rewards are estimated in such a way that it is inexpedient to
run PoA emulators on the hardware suitable for PoW or PoS.
The authors have designed a reward and difficulty assign-
ment system, Neuro, current neural network, inspired by [86].
Neuro utilizes historical blockchain data to predict the
required rewards and difficulties for each new cycle. As soon
as a cycle is completed, the statistics of that cycle are used
to improve the network’s next predictions. In order to make
these predictions, a variation on a type of neural network that
has a selective long-term memory was applied: a recurrent
neural network. For the non-recurrent neural network, each
forward cycle starts with a clean state, and neurons have val-
ues that originate only from weighed connections to neurons
in the previous layers (or inputs). A recurrent neural network
is a network where the result of a neuron activation, the state,
affects the next forward cycle of the network.
This section provides a brief overview of the developed
protocols. More details on the implementation could be
found in [87], more recent versions of protocols (if any
changes) would also be available via the link.
Each k-block has its unique IDkestimated according to
correct execution of function H() as
where His the desired hashing function.
The main requirement of the protocol is resistance against
the repetitive selection of the same miner during a series of
sessions, i.e., improved randomization, and protocol should
be executed either by a group of PoS nodes or all the available
ones but the selection rule is different for each execution.
To exclude the possibility of restarting elections by dis-
gruntled PoS miners, the result should be pseudo-random but
directly related to the number of current k-block and list of
voters. A series of assumptions are thus introduced:
1) All PoS miners in the current system state can compile
a list of all PoSs. In this case, all sets of identifiers will
be obtained identically and ordered lexicographically.
2) In the course of the routing procedures, each PoS
miner compiles a list of currently active PoS. At the
same time, the lists of participants differ by no more
than 10%. The list is stored as a binary vector:
VPoS =(0,1,1,1,0,...,1), where the number of
positions coincides with the size of the list from item
1, where 0 means that the participant with the given
identifier is inactive, and 1 that it is active.
With this list and its associated vector, each node can vote.
Stage A: After the list is constructed, each partici-
pant (PoS miner) calculates the hashing function
r=H(IDk|PoS1|. . . PoSN)
where Hmax =max H(IDk|PoS1|. . . |PoSN) and PoSiis
PoS ID from the list.
Therefore, the voting is further based on rand on com-
paring it to a newly generated discrete random variable
in the same bound. Thus, each PoSireceives a proba-
bilistic value based on its public rating. The sum of all
PoS probabilities should be equal to 1. After that, the
probabilities are logically interpreted into intervals on
the section from 0 to 1, and the tagged PoS node is
selected if ris located in its interval.
Stage B: After the tagged PoS was selected (LPoS
status), the voter calculates the corresponding publica-
tion public key and transmits the ‘salted’ secret key
share to selected LPoS. After one PoS receives at least
kof shares (basically, those have the same list on
their side), the secret key is generated as described
in Algorithm V-B.
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Stage C: LPoS forms a header of the future block after
the session key is received according to Algorithm V-B.
The entry is formed from the k-block number and voting
list signed with the session key. Thus, it becomes possi-
ble to validate LPoS rights and distribute rewards.
The main requirements are: keys could only be used once;
keys should be distributed securely; any user could not gen-
erate keys; and keys do not contain any information related
to PoS miner secret keys.
The protocol is executed for LPoS =PoSiaccordingly.
Each PoS has its pair of keys PKPoSi,SKPoSidirectly related
to its wallet.
Next, the session key PKLPoS is generated for leading PoS.
It will be further utilized for the microblocks signature and,
thus, would be split into shares and distributed between PoAs.
PKLPoS is defined by kblock present in current session and
IDLPoS.IDLPoS is selected as PKLPoS or a function of this key.
PKLPoS and SKLPoS would be thus selected as
PKLPoS =H1(blockk||IDLPoS)=Q,(3)
SKLPoS =ssiQ,(4)
where H1 – is a mapping function described in Algorithm 1,
Qis an element of G1, and ssi,is obtained by Algorithm 2.
SKLPoS is generated by PoS nodes according to the dis-
tributed ID-based cryptographic PKG method [88] by kof
nschema, which considers the collision resolution for cases
when more that one leader is selected. After the key is gener-
ated PoS can group and sign the transactions and distributed
those to applicable PoAs.
Algorithm 1 Initialization of ID-Based Schema With Dis-
tributed PKG
1: Define groups:
2: Define G1 as a cyclic group of order q(group of
points on elliptic curve);
3: Define multiplicative group G2;
4: Define functions:
5: H1:(0,1)G1;
6: H2:G2(0,1);
7: H3:(0,1)Zq;
8: e:G1×G1G2 (bilinear mapping);
9: Define Master Secret Key (MSK) as sZq;
10: Define P: generator of G1;
11: Define Master Public Key (MPK) as sP.
Algorithm 2 PKG (k,n) Master Secret Key Splitting
1: Generate random polynomial in residue field q:
deg(φ(x)) =k1, φ(0) =s;
2: Each participant (PoS) receives its key share of Master
Secret Key ssi=φ(IDi)mod q.
Algorithm 3 Session Key SKLPoS Generation for LPoS
1: Each of kparticipants calculates equation 3.
2: Transmits its ssi·PKLPoS and IDito LPoS.
Algorithm 4 Secret Key Recovery
1: LPoS is calculating SLLPoS based on the received from
Algorithm 3data as
2: SKLPoS =Pk
i=1λ(IDi,0)(ssiPKLPoS)=sQ, where
λ(IDi,0) is a Lagrange coefficient generated per coalition
for each user IDiand 0.
The coalition of PoAs is selected after a new set of trans-
actions is collected is published. It is selected based on
constant NPoA per node and the corresponding ID such that
H(PoAID)=H(kblock||i),i=1,...,NPoA. Therefore,
each node has an opportunity to verify if its ID is in the group
fast, while brute-force attack on the ID is a computationally
complex task.
The main requirements for the protocol are simultaneous
and independent execution of the coalition members; data
exchange minimization; in-block additional data minimiza-
tion; and confirmation of the participation in the verification.
Each PoA verifies if it is applicable for new microblock
verification V-C after new k-block header is published. In
case applicable, it verifies the assigned microblock Mbased
on the selected transaction with a predefined size. After Mis
verified, PoA adds the following data to it: PoAID , k-block
number. Next, it is signed by its’ SKPoA and immediately
published (returned to LPoS).
After Algorithm V-A was executed, and the new session key
was generated with Algorithm V-B, LPoS starts to assure the
Stage A: After PoAs have signed the corresponding
microblocks, LPoS is collecting those from the network.
LPoS is verifying the k-block number and verifies if
PoAs are in the coalition of this block.
Stage B: LPoS verifies the validity of transactions in the
microblock based on the ledger.
Stage C: In case the verification succeeds, each
microblock is signed with the session kety SKLPoS from
Algorithm V-B according to Algorithm 5.
Meanwhile, PoS miners are in standby mode until the
required number of transactions is collected, and generate
final macroblock from all the obtained microblocks to be
distributed to PoWs for the actual addition to the blockchain.
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Algorithm 5 Microblock Signature Protocol
1: LPoS generates rfrom Zq;
2: Calculates R=rP and
S=SKLPoS +r H1(M||IDLPoS ),(5)
where SKLPoS =sQ is obtained with Algorithm 4,H1
with Algorithm 1, and Mis selected microblock.
3: Adds (R,S) to the macroblock.
The main goal of the protocol is to verify any microblock at
any time, and the requirements are: it should be executable
at any node; it should be based only on publicly available
information. Two signatures verify each microblock: the first
one is the signature of PoA node, that verified the correspond-
ing microblock, and the second one is the signature of related
LPoS miner. The verification procedure is made according to
Algorithm 6.
Algorithm 6 Cryptographic Microblock Verification Proto-
1: The verifying node check the k-block number, and then
that the PoA-miner is a member of the group of selected
PoAs for this session and its signature.
2: It calculates PKLPoS according to equation (3).
3: The verifying node checks the signature of the
microblock Rand Sby
e(P,S)=e(MPK,PKLPoS =Q)·e(R,H1(M||IDLPoS )),
where Pis a generator of G1, MPK is a Master Public
Key and Mis a microblock.
The microblock is assumed as verified if both signatures
are checked successfully.
This phase is executed either whenever the set of PoS min-
ers changes, or during the ledger recalculation, i.e., when
any of the PoS nodes loses the PoS status. The resident
node distributes new key shares. It is also responsible for
the (k,n) relations during the initial system operation stage.
After the system operation is stable, its role is distributed
between PoSs.
When a new PoS node arrives, the new node requests its share
of PKG master secret key. If it has the right, the resident node
responds. Keys to new participants are built and given out by
the resident node, while the system developer or owner acts
in its role. When the parameters are settled, the resident role
can be dissolved in PoS miners. For a new participant node,
its polynomial point is calculated as
ssnew =φ(IDnew)mod q,(7)
where qis the order of the group of points G1.
By efficient integration of the previously developed pro-
tocols, it becomes possible to involve a high number of
recourse-constrained devices in the blockchain operation.
In the next section, the proposed system is compared with
existing ones and analyze it from user experience metrics.
This section briefly outlines the performance evaluation setup
from the hardware perspective and provides the technical
specification of the devices, followed by the description of
the performance campaign.
Various aspects of presently available solutions were taken
into consideration during the development phase. The results
of the analysis are given in Table 1. Overall, most of the
existing projects utilize either PoW or Cloud-like techniques,
and, in the latter case, smartphones are not participating in
the blockchain operation process rather than delegating it to
some other instance in the network. Systems like uPlexa and
MIB actually involve the devices, which is the reason behind
our numerical evaluation targeting those systems.
After the protocols are appropriately described, the next
subsection provides the detailed performance evaluation of
MIB and uPlexa on modern smartphones and tablets along
with the developed system.
For the purpose of this work, we have selected multiple
devices from two categories in order to have a broader
overview of the blockchain integration potential: (i) smart-
phones and (ii) tablets. Both flagship and old models of
devices and operating systems were analyzed, and the cor-
responding specification is given in Table 2. Note, Apple
devices are not analyzed within this work since power-hungry
applications by design are prohibited by subsection 2.4.2 of
App Store Review Guidelines. Most of the devices in each
class have very similar characteristics except for the flagship
models. This paper mainly focuses on user-oriented metrics
since smartphones and tablets aim to provide the best user
experience as the most significant personal device of today.
All measurements were carried out under the same con-
ditions and the corresponding dataset is available at [89].
The device had a display on to simulate user interaction,
as it has the highest power consumption compared to other
smartphone modules [90]. Overall, we analyzed the following
1) Self-discharge with turned on display.
2) Operation with different smartphone-oriented
blockchain techniques.
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TABLE 1. Comparison of existing mobile blockchain projects.
TABLE 2. Selected devices with their corresponding specifications.
3) Different connectivity options:
a) Connected over cellular link (LTE).
b) Connected over WLAN (IEEE 802.11n/2.4GHz).
By selecting this set of scenarios, we cover most of the
smartphone operational states.
This subsection provides the main results obtained during the
performance evaluation campaign.
In the first set of experiments, the main focus is given
to the flagship smartphone Samsung Galaxy S9 as the best
representative for handling the potential negative impact
of blockchain operation. First, currently available mobile
blockchain-related applications and related concepts are
overviewed as described in Section III.
Note, only concepts utilizing the computational power of
the smartphone instead of delegated Cloud computing are
analyzed. Cloud mining has been excluded from the evalua-
tion due to the fact that mobile devices running Electroneum
or Phoneum do not mine neither validate blocks nor perform
any tasks. Additionally, with cloud mining, the application
is not required to stay open, making battery monitoring
According to the results depicted in Fig. 4, the PoA-based
solution proposed in this work contributes only approxi-
mately an additional 5% to the device’s discharge rate caused
by the display utilization. At the same time, the negative
impact of PoW-based strategies (MIB and uPlexa) can reach
up to 45%, i.e., the smartphone’s battery will drain twice
as fast (see Fig. 4b) causing a negative impact on user
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FIGURE 4. Impact of different blockchain techniques on Samsung Galaxy
S9 battery.
experience. In addition to this observation, the temperature
of the battery was measured, and the results are given in
Fig. 4c. According to our measurements, the use of PoW on
a mobile phone will not only negatively affect the discharge
rate of the battery but also will increase its temperature to
FIGURE 5. Comparison of the devices from Table 2.
112oF(44oC), which makes the device practically unusable
and potentially dangerous. The same tests were executed ten
times per concept, and the results fall within the same range
for stable operation (battery level >10%).
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FIGURE 6. Impact of wireless technology selection on Samsung Galaxy S9
While the developed solution proved itself as a promis-
ing one from a user experience perspective, we kept the
evaluation towards its impact on different devices listed
in Table 2. All the studied devices show similar behavior
as Samsung Galaxy S9 in terms of battery output voltage
(see comparison in Figs. 5a and 5b) and discharge rate
(Figs. 5c and 5d), i.e., less then 5% of negative impact.
Interestingly, the plots also provide an observation on the
battery saving mode presence either in the battery controller
around 400 mins interval, i.e., after the output voltage drops
beyond the threshold value, see Fig. 4a self-discharge and the
FIGURE 7. PoA verification time.
proposed system operation scenarios. However, the utiliza-
tion of PoW has such a tremendous impact on the battery
state that this behavior is not visible at all due to a rapid
discharged rate.
Notably, previous tests were executed utilizing the WLAN
interface, i.e., IEEE 802.11n operating at 2.4GHz. Because
handheld smartphone devices are mobile nodes by definition,
the analysis of the cellular utilization impact compared to
WLAN is also provided in this paper. For these measure-
ments, the Samsung Galaxy S9 smartphone was chosen since
the results from other devices, see Fig. 5, prove similar behav-
ior in terms of battery impact.
The second scenario is focused on the comparison of LTE
versus WLAN utilization, the measurements are shown in
Fig. 6. Interestingly, utilization of cellular connection is less
energy efficient compared to WLAN, see Fig. 6b. As was
observed in Fig. 5, joint power consumption PoA operation
over WLAN has an impact of only 5% while switching to
LTE may increase it up to 20%. Interestingly, the selection
of wireless interface does not have any significant impact
on the battery temperature, see Fig. 6c, but only on the
battery lifetime, which allows to execute in on the smartphone
without noticeable impact on the user experience. Moreover,
the proposed system shown itself as a promising instrument
with the battery consumption of the instant messenger level.
Execution time-wise, the involvement of resource-
constrained PoA node in the microblock verification process
is transparent for the user, see Fig. 7. The plot shows two
cases, the left one corresponds for the execution time of a
single PoA node from the moment it receives the transactions
from LPoS until the acknowledgment is sent back (measured
on Galaxy S9). The right one provides measurements related
to the overall PoA involvement process measured from the
LPoS side, i.e., the time from the first message to the first PoA
in the group until the acknowledgment reception from the
last one. The execution was observed 1,000 times, and there
were five random PoA nodes selected for each execution
in the second scenario. According to the measurements,
a single verification requires only 500 ms, excluding the
communications overhead. This pattern is highly visible in
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A. Ometov et al.: Overview on Blockchain for Smartphones
the second scenario. Unpredictable network state, as well as
differences in hardware, has an impact on variance while the
impact on the mean is not significant.
Based on the executed trial, the utilization of PoA-based
solutions on the smartphone itself shows a better perspective
compared to PoW-based ones in terms of user experience
After evaluating the ability to execute the designed primitives
on real devices, this subsection provides the analysis of pri-
mary security and privacy aspects of the designed system.
While providing a quantitative analysis of such a complex
system would require a separate publication, this subsection
provides the following overview.
Security risk assessment can be made qualitatively or
quantitatively, there are some techniques that assist in the
threats analysis. To define whether existing threats relevant to
the system, the penetration testing approach was performed.
By applying this methodology to the top-down system analy-
sis, it becomes evident how the system would react in coping
with emerging threats. The analysis includes specific infor-
mation on vulnerabilities and possible approaches taken to
mitigate each risk.
Utilization of a multi-level structure allows obtaining
greater flexibility and reliability of the blockchain system.
As for general countermeasure, all nodes utilize asymmetric
cryptography for encrypting their communications in order
to avoid Man-in-the-Middle Attacks (MITM), each node
generates a key pair (public and secret key) thus providing
the authentication. In particular, the information provided by
each PoA node of the first and lowest level is authenticated
and simultaneously protected from spoofing by using the
digital signature and secret key. The same applies to LPoS
and PoW node.
The appearance of a malicious PoA node in the system can
be detected by the second-level PoS nodes in the process of
forming the macroblock, which consists of the microblocks
verification executed by PoAs. Proposed voting and selecting
of current LPoS for each successive macroblock prevents
a particular malicious PoS from ‘‘colluding’’ with one or
more PoAs.
The Algorithm V-E for microblocks assurance performed
by PoS nodes provides protection against Double Spending
Attack [91]. Since LPoS verifies the validity of transactions
in the microblock during stage B, any node’s signature ver-
ification can be achieved based on the ledger later on. Any
node will receive a confirmation of a false transaction since
the signature is easy to verify using only the information
about the current block number and the LPoS ID, i.e., no
additional blockchain information is required. An incorrect
signature formation is not possible without the participation
of the LPoS, as well as collusion of almost all PoS (the key
issuance threshold provides this) cannot forge a transaction.
It is also impossible to reuse the transaction and change its
location inside the chain since LPoS is linked only to its
k-block (confirmed by the voting results). The lifetime of
each LPoS keys are limited to one k-block, after which new
elections should be held, and a new key will be issued, i.e., it
will not be possible to use the session key to fake microblocks
in the future.
According to [92], the Majority Attack could be defined
as ‘‘The attacker submits to the merchant/network a trans-
action which pays the merchant, while privately mining a
blockchain fork in which a double-spending transaction is
included instead’’. In the proposed system, the attacker, even
with 100% of PoW miners, does not have a chance to gen-
erate the fork by design. Moreover, the utilization of Ran-
domX ensures random code execution, together with several
memory-hard techniques to minimize the efficiency advan-
tage of specialized hardware. Each transaction must be signed
by a PoA linked to the k-block number, macroblocks with a
set of transactions must be signed by the elected LPoS using a
unique session key, which is generated based on a significant
number of PoS nodes. Thus, the attack becomes exceptionally
complex compared to the conventional power-wise approach.
To form such a hidden fork, it is necessary to completely
capture all three levels of the network being geographically
and logically separated.
Selfish Miner Attack is used to reverse a transaction by
‘‘forking’’ the blockchain one block behind the block the
transaction was included in [93], [94]. In the proposed sys-
tem, the length of a branch is determined by the number of
transactions included in it, and therefore it is not possible
to eliminate out transactions by creating empty branches
without the participation of all three security levels.
From the network perspective, the nodes are highly dis-
tributed not only spatially but also between the logical lay-
ers. That includes public keys for verifying PoS and PoA
signatures and rules for forming nodes associated with each
k-block. This feature makes it difficult to execute Routing
attacks, e.g., to isolate a node or network segment and fake
the traffic by emulating the operation of a large number of
malicious nodes. Moreover, PoS nodes involved in voting
require significant stake, thus making the execution of the
attack not only computational- but also token-wise consum-
ing. So, the Eclipse Attack [95] can only be applied in the
short-term to the weakest PoA clients that can be attracted to
work by creating blocks with a false number, while their work
will not be paid for, but it would not result in a DDoS attack
since their packages will be filtered out without processing
by design.
Sybil Attacks [96] aim at providing multiple identities to
other nodes mainly for data crawling, are not critical in the
proposed system, on the one hand, since transactions are
supposed to be stored in the blockchain by regardlessly and,
on the other hand, high dynamics of the proposed architecture
only provide a temporary view on the network. One of the
countermeasures for future implementation may be a tem-
porary additional node ID based on public IP address, thus,
requiring a massive pool of public addresses to execute the
attack. To highlight, current PoS nodes are publicly listed but
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A. Ometov et al.: Overview on Blockchain for Smartphones
could also lose the status over time due to variations in stake.
Similarly to Sybil attack, NodeID attack could be described
as multiple nodes trying to obtain a specific NodeID for false
information distribution. The attack may be crucial for PoS
operation but is mitigated through the distribution of PKG
between active PoS nodes after the genesis period. Therefore,
a group of PoS nodes is required to provide a new one with
its secret key similarly to voting procedure and session key
Timejacking attack [97] targets at interaction with the sys-
tem counter. In the proposed system, it could be targeted at
slowing down the system operation by either malicious LPoS
or PoA nodes. In the case of LPoS, the system operation
may be affected if the node is reporting to the system that
transactions are discarded, but it will result in the loss of
credibility and a lower probability to receive new transactions
for distribution between PoAs, i.e., decreasing the impact in
the future. In the PoA case, the operation would be affected
by precisely one cycle of the PoA verification since LPoS
would re-select a group of PoAs if even one of them failed
the verification.
Rare Poison Block Attack [98] is aimed at generating a
false block with a timestamp ahead of time along with mali-
cious miner, which should accept the block. The attack is
mitigated by multi-layer architecture involving more nodes
in the verification process, which includes the timestamp
From the data privacy perspective, the system is designed
to provide full transparency of the operation, i.e., k-block data
contains the details about all involved nodes, their actions and
transactions. The node ID (essentially, the node’s public key)
is not based on any real-world identifiable data. However,
the field ‘‘Data’’ in each transaction (see already discusses
k-block structure in Fig. 2) could be encrypted based on the
application needs assuring the data privacy of the selected
transaction, e.g., for smart contracts. Moreover, it provides
an additional overlay layer, which is kept outside the scope
of the basic system operation description.
Overall, the system was designed taking into consideration
the majority of known attacks on similar blockchain systems
while keeping the data transparency and cross-verification
in mind.
Indeed, blockchain systems are incredibly complex compared
to the centralized ones. However, our research reveals that
many practical advantages can be yield with blockchain.
Nevertheless, there are several challenges related to the inte-
gration of blockchain technology within smartphones and
communication networks. Still, engaging future research and
investigation directions remain to be analyzed. This section
aims to bring the reader’s attention to potential challenges that
should be taken into consideration during the development of
future distributed systems and redesigning currently existing
Naturally, distributed systems tend to support a continu-
ally increasing number of devices. However, many existing
projects faced numerous scalability issues, starting with the
pioneering example of Bitcoin [82]. Overall, many modern
blockchains suffer from high processing, storage, and trans-
mission overheads, as well as limited scalability [99], [100].
Therefore, the possibility to avoid this bottleneck should be
carefully taken into consideration during future steps of the
blockchain evolution.
One of the most important goals of blockchain from the
smartphone utilization perspective is enabling interoperabil-
ity between different device vendors. Presently, there may be
at least two ways of said integration since straightforwards
possibility is still far from possible.
The first option is interest from a big smartphone ven-
dor (or OS system developer). Therefore, related protocols
could be integrated as part of the market-available device
significantly reducing the overheads coming from the inte-
gration phase.
The second option is related to additional pressure brought
by the cellular operators willing to offload their expensive
licensed resources. The software could be distributed auto-
matically either with the SIM cards or directly through the
operator’s cloud. This, however, does not eliminate the need
to convince OS developers to provide the essential function-
ality support.
Blockchain developers should carefully consider the limita-
tions of the devices. Even though the devices are already
capable of executing blockchain-related computations, they
still may be developed in a very inefficient way, as shown in
Section VI. Some works have already investigated the pos-
sibility of creating a specifically designed overlay network
suitable for IoT blockchain-based networks [101] and propos-
ing custom DLTs fulfilling the storage and computational
limitations of said constrained devices [102].
Moreover, there are research works being actively devel-
oped in the field of Green Mining, focusing on resource-
constrained devices in terms of more efficient resource
allocation [29]. Another perspective direction for assisting
smartphone-based systems by means of Edge Computing,
especially for PoW concepts [41], e.g., by allowing for intel-
ligent computational and storage offloading. Therefore, the
devices would face a need for transmission vs. computational
trade-off. Smartphones and other wearables thus would aban-
don meaningless puzzle solving by either effectively selecting
to delegate the computation or use lighter solutions, like PoA.
Indeed, current networks utilized by smartphones could
not be described as specifically designed for low latency
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A. Ometov et al.: Overview on Blockchain for Smartphones
operation ones mainly due to the high level of heterogeneity
of short- and long-range wireless technologies and standards.
There is no option to analyze such complex and unpre-
dictable networks in terms of packet propagation delay, which
directly affects the fairness of the blockchain network oper-
ation. Many activities are presently happening in the field
of Ultra-Reliable Low Latency Communications (URLLC),
which is expected to be widely deployed as part of LTE
release 14 [103].
Latency is a severe challenge that restricts blockchain
applications in delay-sensitive scenarios [63]. In the
blockchain-based networking services, the processes of gen-
erating and validating blocks are the primary sources of
latency. Essentially, this is the cost of forming trust in an
untrusted network. One key research challenge is to reduce
latency by lowering the block confirmation time while sat-
isfying the requisite system security and trust required by
the users.
Nonetheless, the operation of the blockchain itself cre-
ates additional load on the communication networks [104],
[105], which should also be carefully considered by
both blockchain systems’ developers and communication
Conventional blockchains are built on the Internet, where
block spreading is executed via wired networks and is often
considered to be of little cost. However, in case operators
would plan to integrate custom blockchain solution operation
on the smartphones/Edge, the latency could be significantly
reduced by keeping the traffic inside the LTE core when-
ever possible.
Mostly, blockchain systems are designed with security, pri-
vacy, and anonymity in mind. However, the evolution of var-
ious blockchain systems has shown the community a variety
of attacks that were growing with the development of the
monetary component of market-available systems.
The number of attacks is vast, including but not limited to
the following. Sybil attacks are depicted as a node presenting
itself with multiple identities to other nodes [106], [107].
When the amount of identities is high enough, the attacker
will become capable of taking over the network. Well known
Distributed Denial of Service (DDoS) attack may be per-
formed on critical nodes [108], e.g., PoSs in order to disrupt
the network operation. Time-related attacks aim at manip-
ulation with the blockchain internal counter values [109].
Those include poisoning [110] and time jacking attacks [111].
In the majority attack [112], [113], the intruder submits a
transaction to the network which pays the merchant, while
privately mining a blockchain fork where a double-spending
transaction is included instead.
Communication-related attacks include Eclipse attack [93],
which aims to take control of the communications of a single
node and force it to accept false data. Partitioning attack splits
the network into two or more disjoint groups. It can be done
by taking control of particular points within the network that
acts as the linking point between two groups followed by the
delay attack, i.e., packet capture and push the packets to an
isolated network segment.
Despite resisting to security threats, assurance of the data
privacy plays a vital role in storing and transmitting the data
without revealing sensitive information of the content origi-
nators [114], [115]. There are several common privacy issues.
First, personal and sensitive information should remain confi-
dential to prevent possible misuse even if stored or delivered
by third parties [116]. The second privacy-related scenario
arises in cloud operations such as data sharing, remote soft-
ware updating, cloud computing, and storage [117]. In reality,
it may not be possible for cloud services providers to be
fully trusted, as cloud servers are expected to access personal
data with explicit permission [118]. Herein, blockchain may
provide a decentralized solution for exchanging data while
ensuring privacy and integrity protection.
Despite various challenges arising from the financial seg-
ment [119], the utilization of blockchain and any resource-
hungry applications on smartphones and wearable devices
are bounded by two main legal aspects. On the one hand,
some regions prohibit the operation with any cryptoto-
kens [120], which may potentially slow down the integration
of blockchain.
On the other hand, smartphone operating systems are
commonly not open-source and aim at increasing the bat-
tery lifetime. It results in the policies that prohibit running
any computationally hungry applications/services on their
devices. The adoption by vendors is very far from being
resolved, and this may significantly decrease the possibility
for easy and on the fly integration.
Besides technological, security, and legal aspects, the devel-
opers should carefully consider the user adoption side of
the coin [121]. In particular, a significant portion of human-
ity does not yet trust virtual tokens as carrying any actual
value. The need for proper education in terms of incentives
and user involvement may still be very challenging. On the
bright side, the ICT community is deeply correlated with
distributed systems, and adding one more natural driver for
the corresponding development may be met positively from
their side.
The number of mobile devices is continuously growing,
however, the computational power of those devices is vastly
underused, mainly due to battery constraints. Numerous
applications could use those FLOPs, and one of them is
blockchain. The design of modern blockchain systems mainly
relies on Proof-of-Work consent aiming to solve the computa-
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A. Ometov et al.: Overview on Blockchain for Smartphones
tional puzzle, which is not suitable for smartphones but there
are a few exceptions.
This paper outlined the main applications of blockchain
technology for smartphones and wearable devices stepping
aside from conventional cryptocurrency perspective compar-
ing existing market-available systems. Next, a set of protocols
coupling together Proof-of-Work, Proof-of-Stake, and Proof-
of-Activity blockchain strategies was proposed aiming to
involve mobile devices in the new block generation process.
The protocol is already implemented in a real-life distributed
test network involving more than 2,500 mobile nodes around
the globe.
The developed system operation was compared with other
similar approaches and concluded that it has a shallow
impact (5%) on user experienced battery consumption com-
pared to regular device operation and other systems (up to
40%) keeping the system secure and transparent privacy-
wise. After that, the main challenges of blockchain adoption
from both user and regulatory perspectives were highlighted.
The future directions and the main mobile blockchain chal-
lenges related to the integration of blockchain-based solutions
on smartphones conclude the paper.
The authors would like to acknowledge Enecuum commu-
nity support in the testing of the developed system. For the
research, the infrastructure of the SIX Center was used.
This paper is an extended version of work by Zhidanov,
K., Bezzateev, S., Afanasyeva, A., Sayfullin, M., Vanurin,
S., Bardinova, Y. and Ometov, A. ‘‘Blockchain Technology
for Smartphones and Constrained IoT Devices: A Future
Perspective and Implementation.’’ In Proceedings of the 21st
Conference on Business Informatics (CBI), Vol. 2, pp. 20-27,
2019. IEEE.
[1] Cisco, ‘‘Global mobile data traffic forecast 2017–2022,’’ Cisco, San Jose,
CA, USA, White Paper, 2019.
[2] S. Hiremath, G. Yang, and K. Mankodiya, ‘‘Wearable Internet of Things:
Concept, architectural components and promises for person-centered
healthcare,’’ in Proc. 4th Int. Conf. Wireless Mobile Commun. Healthcare
(MOBIHEALTH), 2014, pp. 304–307.
[3] X. Wang, Xuan Zha, Wei Ni, Ren Ping Liu, Y Jay Guo, Xinxin Niu,
and Kangfeng Zheng, ‘‘Survey on blockchain for Internet of Things,’
Comput. Commun., vol. 136, pp. 10–29, Feb. 2019.
[4] A. Ometov, ‘‘Social, private, and trusted wearable technology under
Cloud-aided intermittent wireless connectivity,’’ Ph.D. dissertation, Dept.
Electron. Commun. Eng., Tampere Univ. Technol., Tampere, Finland,
[5] Y. Wang, R. Chen, and D.-C. Wang, ‘‘A survey of Mobile Cloud Comput-
ing applications: Perspectives and challenges,’’ Wireless Pers. Commun.,
vol. 80, no. 4, pp. 1607–1623, 2015.
[6] C. R. Merkle, ‘‘Method of providing digital signatures,’’ U.S. Patent
4 309569 A, Sep. 5, 1979.
[7] A. Hari and T. Lakshman, ‘‘The Internet blockchain: A distributed,
tamper-resistant transaction framework for the Internet,’’ in Proc. 15th
ACM Workshop Hot Topics Netw., 2016, pp. 204–210.
[8] F. Hawlitschek, B. Notheisen, and T. Teubner, ‘‘The limits of trust-free
systems: A literature review on blockchain technology and trust in the
sharing economy,’’ Electron. Commerce Res. Appl., vol. 29, pp. 50–63,
May 2018.
[9] R. Beck, J. S. Czepluch, N. Lollike, and S. Malone, ‘‘Blockchain—The
gateway to trust-free cryptographic transactions,’’ inProc. 24th Eur. Conf.
Inf. Syst. (ECIS). Springer, 2016, pp. 1–14.
[10] A. Ometov, V. Petrov, S. Bezzateev, S. Andreev, Y. Koucheryavy,
and M. Gerla, ‘‘Challenges of Multi-Factor Authentication for securing
advanced IoT applications,’IEEE Netw., vol. 33, no. 2, pp. 82–88,
Mar. 2019.
[11] C. Osborne. (Oct. 2019). Spending on Wearable Technology to Surge
to $52 Billion by 2020: Gartner. [Online]. Available:
[12] Statista, Inc. (Oct. 2019). Number of Smartphone Users World-
wide from 2016 to 2021. [Online]. Available: https://www.statista.
[13] (2019). Experts Exchange, Processing Power Compared. [Online]. Avail-
[14] Z. Zheng, S. Xie, H.-N. Dai, W. Chen, X. Chen, J. Weng, and
M. Imran, ‘‘An overview on smart contracts: Challenges, advances
and platforms,’Future Gener. Comput. Syst., vol. 105, pp. 475–491,
Apr. 2020.
[15] R. Pirmagomedov, A. Ometov, D. Moltchanov, X. Lu, R. Kovalchukov,
E. Olshannikova, S. Andreev, Y. Koucheryavy, and M. Dohler, ‘‘Apply-
ing blockchain technology for user incentivization in mmWave-
based mesh networks,’IEEE Access, vol. 8, pp. 50983–50994,
Mar. 2020.
[16] J. Huang, L. Kong, H.-N. Dai, W. Ding, L. Cheng, G. Chen, X. Jin,
and P. Zeng, ‘‘Blockchain based mobile crowd sensing in indus-
trial systems,’IEEE Trans. Ind. Informat., early access, Jan. 2020,
doi: 10.1109/TII.2019.2963728.
[17] D. Frey, M. X. Makkes, P.-L. Roman, F. Taïani, and S. Voulgaris, ‘‘Bring-
ing Secure Bitcoin Transactions to Your Smartphone,’’ in Proc. 15th Int.
Workshop Adapt. Reflective Middleware, 2016, p. 3.
[18] D. Loghin, G. Chen, T. T. A. Dinh, B. C. Ooi, and Y. M. Teo, ‘‘Blockchain
goes green? An analysis of blockchain on low-power nodes,’’ 2019,
arXiv:1905.06520. [Online]. Available:
[19] L. Lao, Z. Li, S. Hou, B. Xiao, S. Guo, and Y. Yang, ‘‘A survey of
IoT applications in blockchain systems: Architecture, consensus, and
traffic modeling,’ACM Comput. Surveys, vol. 53, no. 1, pp. 1–32,
Feb. 2020.
[20] D. Rhodes. (May 2018). Is Mobile Mining Profitable? [Online]. Avail-
[21] S. King and S. Nadal, ‘‘PPcoin: Peer-to-Peer crypto-currency with Proof-
of-Stake,’’ 2012.
[22] A. Kiayias, A. Russell, B. David, and R. Oliynykov, ‘‘Ouroboros: A prov-
ably secure proof-of-stake blockchain protocol,’’ in Proc. Annu. Int.
Cryptol. Conf. Cham, Switzerland: Springer, 2017, pp. 357–388.
[23] I. Bentov, C. Lee, A. Mizrahi, and M. Rosenfeld, ‘‘Proof of Activ-
ity: Extending bitcoin’s Proof of Work via Proof of Stake [extended
abstract]y,’’ ACM SIGMETRICS Perform. Eval. Rev., vol. 42, no. 3,
pp. 34–37, Dec. 2014.
[24] A. Ometov, P. Masek, L. Malina, R. Florea, J. Hosek, S. Andreev,
J. Hajny, J. Niutanen, and Y. Koucheryavy, ‘‘Feasibility characterization
of cryptographic primitives for constrained (wearable) IoT devices,’’ in
Proc. IEEE Int. Conf. Pervasive Comput. Commun. Workshops (PerCom
Workshops), Mar. 2016, pp. 1–6.
[25] K. Zhidanov, S. Bezzateev, A. Afanasyeva, M. Sayfullin, S. Vanurin,
Y. Bardinova, and A. Ometov, ‘‘Blockchain technology for smartphones
and constrained IoT devices: A future perspective and implementa-
tion,’’ in Proc. IEEE 21st Conf. Bus. Informat. (CBI), vol. 2, Jul. 2019,
pp. 20–27.
[26] T.-H. Kim, ‘‘A study of digital currency cryptography for business
marketing and finance security,’’ Asia–Pacific J. Multimedia Ser-
vices Convergent Art, Humanities, Sociol., vol. 6, no. 1, pp. 365–376,
Jan. 2016.
[27] M. Crosby, P. Pattanayak, S. Verma, and V. Kalyanaraman, ‘‘Blockchain
technology: Beyond bitcoin,’Appl. Innov., vol. 2, nos. 6–10, p. 71,
[28] J. Fiaidhi, S. Mohammed, and S. Mohammed, ‘‘EDI with blockchain as
an enabler for extreme automation,’IT Prof., vol. 20, no. 4, pp. 66–72,
Jul. 2018.
[29] X. Ling, J. Wang, T. Bouchoucha, B. C. Levy, and Z. Ding, ‘‘Blockchain
radio access network (B-RAN): Towards decentralized secure radio
access paradigm,’IEEE Access, vol. 7, pp. 9714–9723, 2019.
104012 VOLUME 8, 2020
A. Ometov et al.: Overview on Blockchain for Smartphones
[30] A. Galanopoulos, F. Foukalas, and T. A. Tsiftsis, ‘‘Efficient coexistence
of LTE with WiFi in the licensed and unlicensed spectrum aggrega-
tion,’IEEE Trans. Cognit. Commun. Netw., vol. 2, no. 2, pp. 129–140,
Jun. 2016.
[31] M. Simsek, A. Aijaz, M. Dohler, J. Sachs, and G. Fettweis, ‘‘The 5G-
enabled tactile Internet: Applications, requirements, and architecture,’’ in
Proc. IEEE Wireless Commun. Netw. Conf., Apr. 2016, pp. 1–6.
[32] E. Markova, I. Gudkova, A. Ometov, I. Dzantiev, S. Andreev,
Y. Koucheryavy, and K. Samouylov, ‘‘Flexible spectrum management in
a smart city within Licensed Shared Access framework,’’ IEEE Access,
vol. 5, pp. 22252–22261, 2017.
[33] H.-J. Kwon, J. Jeon, A. Bhorkar, Q. Ye, H. Harada, Y. Jiang, L. Liu,
S. Nagata, B. L. Ng, T. Novlan, J. Oh, and W. Yi, ‘‘Licensed-assisted
access to unlicensed spectrum in LTE release 13,’’ IEEE Commun. Mag.,
vol. 55, no. 2, pp. 201–207, Feb. 2017.
[34] H.-N. Dai, Z. Zheng, and Y. Zhang, ‘‘Blockchain for Internet of Things:
A survey,’’ IEEE Internet Things J., vol. 6, no. 5, pp. 8076–8094,
Oct. 2019.
[35] B. Mafakheri, T. Subramanya, L. Goratti, and R. Riggio, ‘‘Blockchain-
based infrastructure sharing in 5G small cell networks,’’ in Proc. 14th
Int. Conf. Netw. Service Manage. (CNSM), 2018, pp. 313–317.
[36] J. Backman, S. Yrjölä, K. Valtanen, and O. Mämmelä, ‘‘Blockchain
network slice broker in 5G: Slice leasing in factory of the future use
case,’’ in Proc. Internet Things Bus. Models, Users, Netw., Nov. 2017,
pp. 1–8.
[37] K. Fan, Y. Ren, Y. Wang, H. Li, and Y. Yang, ‘‘Blockchain-based efficient
privacy preserving and data sharing scheme of content-centric network in
5G,’IET Commun., vol. 12, no. 5, pp. 527–532, Mar. 2018.
[38] Y. Ren, Y. Liu, S. Ji, A. K. Sangaiah, and J. Wang, ‘‘Incentive mechanism
of data storage based on blockchain for wireless sensor networks,’Mobile
Inf. Syst., vol. 2018, pp. 1–10, Aug. 2018.
[39] S. Xie, Z. Zheng, W. Chen, J. Wu, H.-N. Dai, and M. Imran, ‘‘Blockchain
for Cloud exchange: A survey,’Comput. Electr. Eng., vol. 81, Jan. 2020,
Art. no. 106526.
[40] M. Liu, F. R. Yu, Y. Teng, V. C. M. Leung, and M. Song, ‘‘Joint computa-
tion offloading and content caching for wireless blockchain networks,’’ in
Proc. IEEE INFOCOM Conf. Comput. Commun. Workshops (INFOCOM
WKSHPS), Apr. 2018, pp. 517–522.
[41] Z. Xiong, Y. Zhang, D. Niyato, P. Wang, and Z. Han, ‘‘When mobile
blockchain meets edge computing,’IEEE Commun. Mag., vol. 56, no. 8,
pp. 33–39, Aug. 2018.
[42] G. Kumar, R. Saha, M. K. Rai, R. Thomas, and T.-H. Kim, ‘‘Proof-of-
Work consensus approach in blockchain technology for cloud and fog
computing using maximization-factorization statistics,’IEEE Internet
Things J., vol. 6, no. 4, pp. 6835–6842, Aug. 2019.
[43] L. Jiang, S. Xie, S. Maharjan, and Y. Zhang, ‘‘Joint transaction relay-
ing and block verification optimization for blockchain empowered D2D
communication,’IEEE Trans. Veh. Technol., vol. 69, no. 1, pp. 828–841,
Jan. 2020.
[44] A. Rao Kabbinale, E. Dimogerontakis, M. Selimi, A. Ali, L. Navarro,
A. Sathiaseelan, and J. Crowcroft, ‘‘Blockchain for economically sus-
tainable wireless mesh networks,’’ 2018, arXiv:1811.04078. [Online].
[45] Y. Yao and T. Xie, ‘‘A blockchain based authentication mechanism in
wireless local area network,’’ in Proc. Int. Conf. Comput., Netw., Com-
mun. Inf. Syst. (CNCI), 2019, pp. 227–231.
[46] T. Sanda and H. Inaba, ‘‘Proposal of new authentication method in Wi-Fi
access using bitcoin 2.0,’’ in Proc. IEEE 5th Global Conf. Consum.
Electron., Oct. 2016, pp. 1–5.
[47] Y. Niu, L. Wei, C. Zhang, J. Liu, and Y. Fang, ‘‘An anonymous and
accountable authentication scheme for Wi-Fi hotspot access with the bit-
coin blockchain,’’ in Proc. IEEE/CIC Int. Conf. Commun. China (ICCC),
Oct. 2017, pp. 1–6.
[48] C. Li, Q. Wu, H. Li, and J. Liu, ‘‘Trustroam: A novel blockchain-based
cross-domain authentication scheme for Wi-Fi access,’’ inProc. Int. Conf.
Wireless Algorithms, Syst., Appl. Cham, Switzerland: Springer, 2019,
pp. 149–161.
[49] S. Raju, S. Boddepalli, S. Gampa, Q. Yan, and J. S. Deogun, ‘‘Identity
management using blockchain for cognitive cellular networks,’’ in Proc.
IEEE Int. Conf. Commun. (ICC), May 2017, pp. 1–6.
[50] A. Mühle, A. Grüner, T. Gayvoronskaya, and C. Meinel, ‘‘A survey on
essential components of a self-sovereign identity,’’ Comput. Sci. Rev.,
vol. 30, pp. 80–86, Nov. 2018.
[51] Q. Stokkink and J. Pouwelse, ‘‘Deployment of a blockchain-based self-
sovereign identity,’’ in Proc. IEEE Int. Conf. Internet Things (iThings),
IEEE Green Comput. Commun. (GreenCom), IEEE Cyber., Phys.
Social Comput. (CPSCom) IEEE Smart Data (SmartData), Jul. 2018,
pp. 1336–1342.
[52] J. Leimgruber, A. Meier, and J. Backus, ‘‘Bloom protocol: Decentralized
credit scoring powered by Ethereum and IPFS,’’ Early Community Draft
Version 0.3 Subject to Change, Longwood, FL, USA, White Paper,
Jan. 2018.
[53] S. Homayoun, A. Dehghantanha, R. M. Parizi, and K.-K.-R. Choo, ‘‘A
blockchain-based framework for detecting malicious mobile applications
in app stores,’’ in Proc. IEEE Can. Conf. Electr. Comput. Eng. (CCECE),
May 2019, pp. 1–4.
[54] W. Meng, W. Li, and L. Zhu, ‘‘Enhancing medical smartphone
networks via blockchain-based trust management against insider
attacks,’IEEE Trans. Eng. Manag., early access, Jul. 2019,
doi: 10.1109/TEM.2019.2921736.
[55] Z. Yang, K. Yang, L. Lei, K. Zheng, and V. C. M. Leung, ‘‘Blockchain-
based decentralized trust management in vehicular networks,’IEEE
Internet Things J., vol. 6, no. 2, pp. 1495–1505, Apr. 2019.
[56] L. Li, J. Liu, L. Cheng, S. Qiu, W. Wang, X. Zhang, and Z. Zhang, ‘‘Cred-
itCoin: A privacy-preserving blockchain-based incentive announcement
network for communications of smart vehicles,’IEEE Trans. Intell.
Transp. Syst., vol. 19, no. 7, pp. 2204–2220, Jul. 2018.
[57] A. Moinet, B. Darties, and J.-L. Baril, ‘‘Blockchain based trust & authen-
tication for decentralized sensor networks,’’ 2017, arXiv:1706.01730.
[Online]. Available:
[58] Z. Gao, L. Xu, G. Turner, B. Patel, N. Diallo, L. Chen, and W. Shi,
‘‘Blockchain-based identity management with mobile device,’’ in Proc.
1st Workshop Cryptocurrencies Blockchains Distrib. Syst. (CryBlock),
2018, pp. 66–70.
[59] P. Garcia, ‘‘Biometrics on the blockchain,’’ Biometric Technol. Today,
vol. 2018, no. 5, pp. 5–7, May 2018.
[60] X. Xu, Q. Liu, X. Zhang, J. Zhang, L. Qi, and W. Dou, ‘‘A blockchain-
powered crowdsourcing method with privacy preservation in mobile envi-
ronment,’IEEE Trans. Comput. Social Syst., vol. 6, no. 6, pp. 1407–1419,
Dec. 2019.
[61] W. Feng and Z. Yan, ‘‘MCS-chain: Decentralized and trustworthy mobile
crowdsourcing based on blockchain,’Future Gener. Comput. Syst.,
vol. 95, pp. 649–666, Jun. 2019.
[62] E. S. Miguel, R. Timmerman, S. Mosquera, E. Dimogerontakis,
F. Freitag, and L. Navarro, ‘‘Blockchain-enabled participatory incentives
for crowdsourced mesh networks,’’ in Proc. Int. Conf. Econ. Grids,
Clouds, Syst., Services. Cham, Switzerland: Springer, 2019, pp. 178–187.
[63] J. Kang, Z. Xiong, D. Niyato, P. Wang, D. Ye, and D. I. Kim,
‘‘Incentivizing consensus propagation in Proof-of-Stake based consor-
tium blockchain networks,’IEEE Wireless Commun. Lett., vol. 8, no. 1,
pp. 157–160, Feb. 2019.
[64] C. Chakrabarti and S. Basu, ‘‘A blockchain based incentive scheme for
post disaster opportunistic communication over DTN,’’ in Proc. 20th Int.
Conf. Distrib. Comput. Netw., Jan. 2019, pp. 385–388.
[65] M. Attaran and A. Gunasekaran, ‘‘Blockchain for Gaming,’’ in Applica-
tions of Blockchain Technology in Business. Cham, Switzerland: Springer,
2019, pp. 85–88.
[66] H. Y. Yuen, F. Wu, W. Cai, H. C. B. Chan, Q. Yan, and V. C. M. Leung,
‘‘Proof-of-play: A novel consensus model for blockchain-based Peer-to-
Peer gaming system,’’ in Proc. ACM Int. Symp. Blockchain Secure Crit.
Infrastruct., 2019, pp. 19–28.
[67] G. Agrawal. (Jul. 2018). How Blockchain Is Completely Disrupting The
Gaming Industry. [Online]. Available:
[68] T. Min, H. Wang, Y. Guo, and W. Cai, ‘‘Blockchain games:
A survey,’’ 2019, arXiv:1906.05558. [Online]. Available:
[69] N. Chalaemwongwan and W. Kurutach, ‘‘State of the art and challenges
facing consensus protocols on blockchain,’’ in Proc. Int. Conf. Inf. Netw.
(ICOIN), 2018, pp. 957–962.
[70] A. Gervais, G. O. Karame, K. Wüst, V. Glykantzis, H. Ritzdorf, and
S. Capkun, ‘‘On the security and performance of Proof of Work
blockchains,’’ in Proc. ACM SIGSAC Conf. Comput. Commun. Secur.,
Oct. 2016, pp. 3–16.
[71] D. Mingxiao,M. Xiaofeng, Z. Zhe, W. Xiangwei, and C. Qijun, ‘‘A review
on consensus algorithm of blockchain,’’ in Proc. IEEE Int. Conf. Syst.,
Man, Cybern. (SMC), Oct. 2017, pp. 2567–2572.
VOLUME 8, 2020 104013
A. Ometov et al.: Overview on Blockchain for Smartphones
[72] M. Vukolić, ‘‘The quest for scalable blockchain fabric: Proof-of-Work
vs. BFT replication,’’ in Proc. Int. Workshop Open Problems Netw. Secur.
Zürich, Switzerland: Springer, 2015, pp. 112–125.
[73] A Medium Corporation. (Nov. 2018). MIB Mining Across the World.
[Online]. Available:
[74] MIB Team. (Jul. 2018). Mobile Integrated Blockchain Coin—MIB
White Paper. [Online]. Available:
[75] Constantine Pappas. (Aug. 2019). Enablement for Personal
Permission-less Blockchains on Proof-of-Transaction, Mobile
Devices and Inter-Planetary File System. [Online]. Available:
[76] Electroneum Ltd. (2019). A Revolutionary New Digital Payments Ecosys-
tem. [Online]. Available:
[77] Phoneum. (Dec. 2019). Mobile Only Cryptocurrency: White Paper.
[Online]. Available:
[78] A. Shamir, ‘‘Identity-based cryptosystems and signature schemes,’’ in
Proc. Workshop Theory Appl. Cryptograph. Techn. Berlin, Germany:
Springer, 1984, pp. 47–53.
[79] C. Cocks, ‘‘An identity based encryption scheme based on quadratic
residues,’’ in Proc. IMA Int. Conf. Cryptogr. Coding. Berlin, Germany:
Springer, 2001, pp. 360–363.
[80] A. Shamir, ‘‘How to share a secret,’Commun. ACM, vol. 22, no. 11,
pp. 612–613, Nov. 1979.
[81] A. Ometov, K. Zhidanov, S. Bezzateev, R. Florea, S. Andreev, and
Y. Koucheryavy, ‘‘Securing network-assisted direct communication:
The case of unreliable cellular connectivity,’’ in Proc. IEEE 14th Int.
Conf. Trust, Secur. Privacy Comput. Commun. (TrustCom), Aug. 2015,
pp. 826–833.
[82] S. Nakamoto, Bitcoin: A Peer-to-Peer Electronic Cash System. 2008.
[83] A. Shevchenko, Monero Penalizes GPU and ASIC Mining with RandomX
Upgrade. in Decentral Media Crypto Briefing. Dec. 2019.
[84] E. Heilman and T. Dryja, ‘‘IOTA vulnerability report: Cryptanalysis of the
CURL hash function enabling practical signature forgery attacks on the
IOTA Cryptocurrency [OL],’’ MIT Media Lab, Cambridge, MA, USA,
Tech. Rep., Sep. 2017.
[85] A. B. Kahn, ‘‘Topological sorting of large networks,’’ Commun. ACM,
vol. 5, no. 11, pp. 558–562, Nov. 1962.
[86] H. Jang and J. Lee, ‘‘An empirical study on modeling and prediction
of bitcoin prices with Bayesian neural networks based on blockchain
information,’IEEE Access, vol. 6, pp. 5427–5437, 2018.
[87] ENECUUM HK Limited. (2019). Dynamic Mobile Blockchain With
Enecuum: A Synergy of Proof-of-Work, Proof-of-Activity, and Proof-of-
Stake. [Online]. Available:
[88] C. Gentry and A. Silverberg, ‘‘Hierarchical ID-based cryptography,’’
in Proc. Int. Conf. Theory Appl. Cryptol. Inf. Secur. Berlin, Germany:
Springer, 2002, pp. 548–566.
[89] Y. Bardinova. (Apr. 2020). A Dataset of Existing Mobile Blockchain Mea-
surements Executed on Smartphones. [Online]. Available: https://github.
[90] X. Chen, N. Ding, A. Jindal, Y. C. Hu, M. Gupta, and R. Vannithamby,
‘‘Smartphone energy drain in the wild: Analysis and implications,’’ ACM
SIGMETRICS Perform. Eval. Rev., vol. 43, no. 1, pp. 151–164, Jun. 2015.
[91] G. O. Karame, E. Androulaki, M. Roeschlin, A. Gervais, and S. Čapkun,
‘‘Misbehavior in bitcoin: A study of double-spending and accountabil-
ity,’’ ACM Trans. Inf. Syst. Secur., vol. 18, no. 1, pp. 1–32, Jun. 2015.
[92] J. Daniel, G. Ducatel, and T. Dimitrakos, ‘‘Mitigating blockchain attack,’
U.S. Patent 9 807106, Oct. 31, 2017.
[93] K. Nayak, S. Kumar, A. Miller, and E. Shi, ‘‘Stubborn mining: Generaliz-
ing selfish mining and combining with an eclipse attack,’’ in Proc. IEEE
Eur. Symp. Secur. Privacy (EuroS&P), Mar. 2016, pp. 305–320.
[94] A. Sapirshtein, Y. Sompolinsky, and A. Zohar, ‘‘Optimal selfish mining
strategies in bitcoin,’’ in Proc. Int. Conf. Financial Cryptogr. Data Secur.
Washington, DC, USA: Springer, 2016, pp. 515–532.
[95] E. Heilman, A. Kendler, A. Zohar, and S. Goldberg, ‘‘Eclipse attacks
on bitcoin’s Peer-to-Peer network,’’ in Proc. 24th USENIX Secur. Symp.
(USENIX Secur.), 2015, pp. 129–144.
[96] S. Zhang and J.-H. Lee, ‘‘Double-spending with a Sybil attack in the
bitcoin decentralized network,’IEEE Trans. Ind. Informat., vol. 15,
no. 10, pp. 5715–5722, Oct. 2019.
[97] D. Meshkov, A. Chepurnoy, and M. Jansen, ‘‘Short paper: Revisiting
difficulty control for blockchain systems,’’ in Data Privacy Manage-
ment, Cryptocurrencies and Blockchain Technology. Cham, Switzerland:
Springer, 2017, pp. 429–436.
[98] J. Kume, M. Abe, and T. Okamoto, ‘‘Lottery protocol for cryptocur-
rency,’’ in Proc. SCIS, 2015, pp. 1–5.
[99] Z. Zheng, S. Xie, H.-N. Dai, X. Chen, and H. Wang, ‘‘Blockchain chal-
lenges and opportunities: A survey,’’ Int. J. Web Grid Services, vol. 14,
no. 4, pp. 352–375, 2018.
[100] Q. Zhou, H. Huang, Z. Zheng, and J. Bian, ‘‘Solutions to scalabil-
ity of blockchain: A survey,’’ IEEE Access, vol. 8, pp. 16440–16455,
[101] A. Dorri, S. S. Kanhere, and R. Jurdak, ‘‘Towards an optimized
blockchain for IoT,’’ in Proc. 2nd Int. Conf. Internet-Things Design
Implement., Apr. 2017, pp. 173–178.
[102] F. Buccafurri, G. Lax, S. Nicolazzo, and A. Nocera, ‘‘Overcoming limits
of blockchain for IoT applications,’’ in Proc. 12th Int. Conf. Availability,
Rel. Secur., 2017, p. 26.
[103] C. Hoymann, D. Astely, M. Stattin, G. Wikstrom, J.-F. Cheng,
A. Hoglund, M. Frenne, R. Blasco, J. Huschke, and F. Gunnarsson, ‘‘LTE
release 14 outlook,’IEEE Commun. Mag., vol. 54, no. 6, pp. 44–49,
Jun. 2016.
[104] P. Danzi, A. E. Kalor, C. Stefanovic, and P. Popovski, ‘‘Analysis of the
communication traffic for blockchain synchronization of IoT devices,’’
in Proc. IEEE Int. Conf. Commun. (ICC), May 2018, pp. 1–7.
[105] M. Scherer, ‘‘Performance and scalability of blockchain networks and
smart contracts,’’ Dept. Comput. Sci., Umeå Univ., Sweden, Umeå,
Tech. Rep. 136470, 2017.
[106] P. Otte, M. de Vos, and J. Pouwelse, ‘‘TrustChain: A sybil-resistant scal-
able blockchain,’Future Gener. Comput. Syst., vol. 107, pp. 770–780,
Jun. 2020.
[107] S. Kim, Y. Kwon, and S. Cho, ‘‘A survey of scalability solutions on
blockchain,’’ in Proc. Int. Conf. Inf. Commun. Technol. Converg. (ICTC),
Oct. 2018, pp. 1204–1207.
[108] R. Vishwakarma and A. K. Jain, ‘‘A survey of DDoS attacking techniques
and defence mechanisms in the IoT network,’Telecommun. Syst., vol. 73,
no. 1, pp. 3–25, Jan. 2020.
[109] J. Moubarak, E. Filiol, and M. Chamoun, ‘‘On blockchain security and
relevant attacks,’’ in Proc. IEEE Middle East North Afr. Commun. Conf.
(MENACOMM), Apr. 2018, pp. 1–6.
[110] K. Sarpatwar, R. Vaculin, H. Min, G. Su, T. Heath, G. Ganapavarapu,
and D. Dillenberger, ‘‘Towards enabling trusted artificial intelligence
via blockchain,’’ in Policy-Based Autonomic Data Governance. Cham,
Switzerland: Springer, 2019, pp. 137–153.
[111] C. A. Vyas and M. Lunagaria, ‘‘Security concerns and issues for bit-
coin,’’ in Proc. Nat. Conf. Workshop Bioinf. Comput. Biol., NCWBCB,
[112] M. Saad, J. Spaulding, L. Njilla, C. Kamhoua, S. Shetty, D. Nyang,
and A. Mohaisen, ‘‘Exploring the attack surface of blockchain:
A systematic overview,’’ 2019, arXiv:1904.03487. [Online]. Available:
[113] H. Watanabe, S. Fujimura, A. Nakadaira, Y. Miyazaki, A. Akutsu, and
J. Kishigami, ‘‘Blockchain contract: Securing a blockchain applied to
smart contracts,’’ in Proc. IEEE Int. Conf. Consum. Electron. (ICCE),
Jan. 2016, pp. 467–468.
[114] G. Zyskind, O. Nathan, and A. Pentland, ‘‘Decentralizing privacy: Using
blockchain to protect personal data,’’ in Proc. IEEE Secur. Privacy Work-
shops, May 2015, pp. 180–184.
[115] C. Esposito, A. D. Santis, G. Tortora, H. Chang, and K.-K. R.
Choo, ‘‘Blockchain: A panacea for healthcare cloud-based data secu-
rity and privacy?’IEEE Cloud Comput., vol. 5, no. 1, pp. 31–37,
Jan./Feb. 2018.
[116] M. A. Khan and K. Salah, ‘‘IoT security: Review, blockchain solutions,
and open challenges,’Future Gener. Comput. Syst., vol. 82, pp. 395–411,
May 2018.
[117] X. Liang, S. Shetty, D. Tosh, C. Kamhoua, K. Kwiat, and L. Njilla,
‘‘ProvChain: A blockchain-based data provenance architecture in
cloud environment with enhanced privacy and availability,’’ in Proc.
17th IEEE/ACM Int. Symp. Cluster, Cloud Grid Comput. (CCGRID),
May 2017, pp. 468–477.
[118] N. Kshetri, ‘‘Blockchain’s roles in strengthening cybersecurity and pro-
tecting privacy,’’ Telecommun. Policy, vol. 41, no. 10, pp. 1027–1038,
Nov. 2017.
[119] E. Saiedi, A. Broström, and F. Ruiz, ‘‘Global drivers of cryptocurrency
infrastructure adoption,’’ in Proc. Small Bus. Econ., 2020, pp. 1–54.
[120] G. Prayogo, ‘‘Bitcoin, regulation and the importance of national legal
reform,’Asian J. Law Jurisprudence, vol. 1, no. 1, pp. 1–9, 2018.
[121] F. Shahzad, G. Xiu, J. Wang, and M. Shahbaz, ‘‘An empirical investiga-
tion on the adoption of cryptocurrencies among the people of mainland
China,’Technol. Soc., vol. 55, pp. 33–40, Nov. 2018.
104014 VOLUME 8, 2020
A. Ometov et al.: Overview on Blockchain for Smartphones
received the D.Sc. (Tech.) and M.Sc. degrees
from Tampere University of Technology (TUT),
Finland, in 2018 and 2016, respectively. He is cur-
rently a Postdoctoral Research Fellow with Tam-
pere University (TAU), Finland. He is also work-
ing on H2020 MCSA ITN/EJD A-WEAR Project.
His research interests are wireless communica-
tions, information security, blockchain technology,
and wearable applications.
YULIA BARDINOVA received the B.Sc. degree
in information security from the Saint Petersburg
State University of Telecommunications, in 2020.
She is currently pursuing the M.Sc. degree with
Tampere University (TAU), Finland. She is also a
QA Engineer with Enecuum. Her research inter-
ests are distributed systems and protocol develop-
and M.S. degrees in information systems from
the Saint Petersburg State University of aerospace
instrumentation (SUAI), in 2001 and 2003, respec-
tively. Since 2003, she has been on the faculty
of Information Systems and Information Security,
SUAI. She is currently with ITMO University.
She participated in and managed joint Research
and Development projects of SUAI with Samsung,
Intel, and EMC, in the field of information security
and optimization of resource allocation algorithms in data storage systems.
Her research interests include coding theory, cryptography, and distributed
storage systems.
PAVEL MASEK (Member, IEEE) received the
M.Sc. and Ph.D. degrees in electrical engineer-
ing from the Faculty of Electrical Engineering
and Communication, Brno University of Technol-
ogy (BUT), Czech Republic, in 2013 and 2017,
respectively. He is currently a Researcher with the
Department of Telecommunications, BUT. He is
also co-supervising the WISLAB Research Group,
where his current research interests include vari-
ous aspects in the area of heterogeneous wireless
communication networks and systems, the Internet of Things, and Industry
4.0-Driven Research Projects. He has coauthored more than 90 research
works on a variety of networking-related topics in internationally recognized
venues, including those published in the IEEE Communications Magazine,
as well as several technology products.
KONSTANTIN ZHIDANOV received the Engi-
neering degree from the State University of
Airspace Instrumentation (SUAI), Russia, in 2006.
He is currently the Tech Lead of Enecuum Lim-
ited. His major research interests are information
security, blockchain technology, and information
SERGEY VANURIN received the degree in
applied mathematics as a specialist from Saint-
Petersburg State University, in 2009, and the mas-
ter’s degree from Saint-Petersburg Institute for
Informatics and Automation, Russian Academy
of Sciences. He worked as a Software Engi-
neer and an IT Project Manager with Banking,
UAV, and DLT fields. He is currently the Project
Manager with Enecuum Ltd. As a Haskell pro-
gramming language enthusiast, he is currently
teaching a course of Haskell with ITMO University. His research interest
is category theory.
MIKHAIL SAYFULLIN received the Specialist
degree from the Bonch-Bruevich Saint-Petersburg
State University of Telecommunications, in 2002.
He is currently the CEO of Enecuum Limited. His
research interests include blockchain technology,
distributed applications, and protocols develop-
Member, IEEE) received the double M.Sc. degree
in engineering from the University of Applied
Sciences Technikum Wien, Austria, and the M.Sc.
degree in business informatics from National
Research University Higher School of Economics,
Russia, in 2019. She is currently a Postdoctoral
Researcher with TAU, as part of H2020 MCSA
ITN/EJD A-WEAR project. Her most research
interests are data privacy, location privacy, indoor
and outdoor positioning, and wearable technologies.
is currently a Professor with the Department of
Innovations and Business in IT, School of Busi-
ness Informatics, Faculty of Business and Manage-
ment, National Research University Higher School
of Economics. He is also a specialist in wireless
data transmission and IT. He is the Vice-Chair of
the Special Interest Group on IoT at the Internet
SERGEY BEZZATEEV (Member, IEEE) received
the Ph.D. and Dr.Sc. degrees, in 1987 and
2011, respectively. From1993 to 1995, he was a
Researcher with the Nagoya University, Japan.
Since 1995, he was an Associate Professor with
the Department of Information Technologies and
Information Security, SUAI. From 2004 till 2007,
he was a Project Leader with the Joint Laboratory
Samsung-SUAI on Information Security in Wire-
less Networks. In 2017, he became a Professor
with the Secure Information Technologies School, ITMO University. He is
currently a Professor and the Head of the Department of Technologies of
Information Security, SUAI. He is also a Professor with ITMO University.
His main research interests include coding theory and cryptography.
VOLUME 8, 2020 104015
... Third, peer-peer trust is maintained through the consensus mechanism, which removes the need for intermediaries that may not be trustworthy. Blockchain finds applications in various areas such as logistics and supply chain [32,33], e-commerce [34], education [35], healthcare [36], governance [37] and others [38]. It can also be used in telecommunication technology [39], stock exchange [40], industrial IoT [41], smart city development [42,43], energy management [44], Unmanned Aerial Vehicles (UAV) [45], and smart grids [46]. ...
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There is an urgent need to control global warming caused by humans to achieve a sustainable future. $CO_2$ levels are rising steadily and while countries worldwide are actively moving toward the sustainability goals proposed during the Paris Agreement in 2015, we are still a long way to go from achieving a sustainable mode of global operation. The increased popularity of cryptocurrencies since the introduction of Bitcoin in 2009 has been accompanied by an increasing trend in greenhouse gas emissions and high electrical energy consumption. Popular energy tracking studies (e.g., Digiconomist and the Cambridge Bitcoin Energy Consumption Index (CBECI)) have estimated energy consumption ranges of 29.96 TWh to 135.12 TWh and 26.41 TWh to 176.98 TWh respectively for Bitcoin as of July 2021, which are equivalent to the energy consumption of countries such as Sweden and Thailand. The latest estimate by Digiconomist on carbon footprints shows a 64.18 Mt$CO_2$ emission by Bitcoin as of July 2021, close to the emissions by Greece and Oman. This review compiles estimates made by various studies from 2018 to 2021. We compare with the energy consumption and carbon footprints of these cryptocurrencies with countries around the world, and centralized transaction methods such as Visa. We identify the problems associated with cryptocurrencies, and propose solutions that can help reduce their energy usage and carbon footprints. Finally, we present case studies on cryptocurrency networks namely, Ethereum 2.0 and Pi Network, with a discussion on how they solve some of the challenges we have identified.
... Most of the gadgets used in blockchain-related activities are specifically developed for mining. Simultaneously, the usage of mobile devices may become an important component of digital commerce blockchain operations [14]. With the development of Bitcoin, blockchain has risen to prominence, and the availability of blockchain on mobile devices has attracted the interest of many. ...
... This study specified current relevant research orientations, researcher gaps research, and commonly encountered challenges, and analyzed the maturity of the research progression. A. Ometov et al.[72] focused specifically on the application of Blockchain for smartphone devices. This study investigated the com-2.3. ...
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The concept of smart cities is increasingly gaining prominence in modern metropolises due to the emergence and spread of embedded and connected smart devices, systems, and technologies in everyday lives, which have created an opportunity to connect every ‘thing’ to the Internet. In the upcoming era of the Internet of Things, the Internet of Vehicles (IOV) will play a crucial role in constructing a smart city. In fact, the IOV has a potential to solve various traffic problems effectively. It is critical for enhancing road utilization, reducing energy consumption and pollution, and improving road safety. Nevertheless, the primary issue regarding the IoV, and in particular to Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I), is establishing secure and instant payments and communications. To respond to this challenge, this work proposes a Blockchain-based solution for establishing secure payment and communication in order to study the use of Blockchain as middle-ware between different participants of intelligent transportation systems. The proposed framework employs Ethereum to develop a solution aimed at facilitating Vehicle-to-Everything (V2X) communications and payments. Moreover, this work qualitatively test the performance and resilience of the proposed systems against common security attacks. Computational tests showed that the proposed solution solved the main challenges of Vehicle-to-X (V2X) communications such as security and centralization.
Bu araştırmada öğretmen adaylarının akıllı telefonların tasarımda güvenlik beklentilerinin ortaya çıkarılması, bu konuda bir ölçme aracı geliştirilmesi ve beklentilerin cinsiyet, kuşak, branş grubu, akıllı telefonu ana kullanım amacı, kullanılan akıllı telefonun işletim sistemi, kullanılan akıllı telefon sayısı, akıllı telefon değiştirme sıklığı ve akıllı telefon segment tercihi olmak üzere sekiz değişken açısından incelenmesi amaçlanmaktadır. Odak grup görüşmeleri, ölçek geliştirme süreci ve ölçek uygulaması araştırmanın aşamalarını oluşturmaktadır. Araştırmanın evreni 2020-2021 akademik yıllarında Türkiye’deki devlet üniversitelerindeki öğretmen adaylarıdır. Tüm veri toplama aşamalarının katılımcıları Eskişehir ilindeki iki üniversitede (Anadolu, Osmangazi) öğrenimlerine devam eden öğretmen adaylarından oluşmaktadır. Araştırma sonuçlarına göre öğretmen adaylarının tasarımda güvenlik beklentileri konusunda “bilgi güvenliği geliştirmeleri” teması ilk sırada gelmektedir. Geliştirme süreci tamamlanan Akıllı Telefonların Tasarımında Güvenlik Beklentileri Ölçeği (ATTGBÖ), “kullanıcıya özgü beklentiler”, “cihaza özgü beklentiler”, “entegrasyon beklentileri”, “sağlığa özgü beklentiler” ve “destek beklentileri” olmak üzere 5 faktör ve 21 maddeden oluşmaktadır. Ölçek uygulamasına göre öğretmen adaylarının akıllı telefonların tasarımında güvenlik beklentileri genel olarak yüksek seviyededir. Belirlenen yedi değişken açısından en az bir boyutta anlamlı bir farklılaşma görülmüştür. “Kullanılan akıllı telefon sayısı” açısından anlamlı bir farklılık bulunmamıştır. Ulaşılan sonuçlar alanyazındaki araştırmalarla birlikte tartışılmış, araştırmacı ve uygulayıcılar için öneriler sunulmuştur. // In this research, it is aimed to reveal the safety expectations of pre-service teachers in the design of smartphones, to develop a measurement tool in this regard and to examine the expectations in terms of eight variables as follows: gender, generation, department group, main purpose of smartphone use, operating system, number of smartphones used, smartphone replacement frequency and smartphone segment preference. Focus group discussions, scale development process and scale application constitute the stages of the research. The universe of the research consists of pre-service teachers who continue their education at state universities in Turkey in the 2020-2021 academic year. Both qualitative and quantitative, the participants of all data collection phases of the research consist of pre-service teachers who continue their education at two universities (Anadolu, Osmangazi) in Eskişehir province. According to the results of the research, the theme of “information security improvements” comes first in terms of pre-service teachers’ safety expectations in design. The final “Safety Expectations in the Design of Smartphones Scale (SEitDoSS)” consists of 21 items and five factors (user-specific expectations, device-specific expectations, integration expectations, health-specific expectations and support expectations). According to the scale application, pre-service teachers’ safety expectations in the design of smartphones are generally high. There was a significant difference in at least one dimension in terms of seven variables and no significant difference according to “number of smartphones used”. The implications of the obtained results were discussed together with the studies in the literature, and suggestions were presented for researchers and practitioners.
With the rapid transformation of the energy sector towards modern power systems represented by smart grids (SGs), microgrids (MG), and distributed generation, blockchain (BC) technology has shown the capability for solving security, privacy, and reliability challenges that hinder progress. Currently, the energy structure is forming a decentralized system that prioritizes customer satisfaction. BC technology undertakes power network stockholders in a secure energy market, transparent transactions, and fair competition and offers promising energy solutions. This paper is a comprehensive review of energy applications using BC integration. Firstly, we introduce the drivers of BC leverage that make it a potentially important component of the power network. Following that, we provide background information on BC and its application in areas other than the energy sector. Subsequently, we discuss studies and sort potential energy applications from various recent papers and surveys that have already adopted BC technology in the energy sector. Then, we summarize the pricing infrastructure for applying BC in the energy sector and identify the requirements to build it. Finally, energy security and privacy challenges based on BC are highlighted, along with potential drawbacks and concerns related to the pricing infrastructure.
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It has long been difficult to create a safe electronic voting system that provides the transparency and flexibility provided by electronic systems while maintaining the fairness and privacy of present voting methods. Voting, especially during elections, is a technique where participants do not trust one another since the system might be attacked not just by an outsider but also by participants themselves (voters and organizers). The traditional methods of voting systems find it challenging to maintain the characteristics of an ideal voting system since there is a chance of tampering with results and disturbing the process itself. As a result, the effectiveness of the voting system is increased by translating the characteristics of an ideal voting system into digital space. It greatly lowers the expense of the elections and the work of the inspectors. In this essay, we'll use the open-source Blockchain technology to suggest a new electronic voting system's architecture. New chances to create new kinds of digital services are being provided by Blockchain. Numerous elements of our life have been altered by Blockchain technology, including the ability to save digital transactions via the Internet, confirm their legitimacy, license them, and provide the greatest level of security and encryption. This system offers a distributed architecture for storing the data, which distributes the data among many servers. In addition to maintaining voter identity outside of the vote count, this technology makes the voting process transparent.
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Le concept de villes intelligentes gagne de plus en plus en importance dans les métropoles modernes en raison de l’émergence et de la diffusion d’appareils, de systèmes et de technologies intelligents embarqués et connectés dans la vie quotidienne, qui ont créé l’opportunité de connecter chaque “chose" à Internet. Dans l'ère à venir de l'Internet des objets, l'Internet des véhicules (IoV) jouera un rôle crucial dans la construction d'une ville intelligente. En fait, l'IoV a le potentiel de résoudre efficacement divers problèmes de trafic. Il est essentiel pour améliorer l'utilisation des routes, réduire la consommation d'énergie et la pollution et améliorer la sécurité routière. Néanmoins, le principal problème concernant l'IoV, et en particulier le Véhicule-à-Véhicule (V2V) et le Véhicule-à-infrastructure (V2I), est l'établissement de paiements et de communications sécurisés et instantanés. Pour répondre à ce défi, ce travail propose une solution basée sur la Blockchain pour mettre en place un paiement et une communication sécurisés afin d'étudier l'utilisation de la Blockchain comme middleware entre différents acteurs des systèmes de transport intelligents.Dans cette étude, nous avons évalué les propriétés les plus importantes de la solution développée, à savoir la consommation de la mémoire et de l’énergie, l’immutabilité, la confidentialité, la cohérence, l’intégrité, le temps d’exécution et le coût. L’objet de cette évaluation est de vérifier la capacité de la plateforme basée sur la Blockchain à assurer une communication efficace et un paiement sécurisé avec l’IoV. Selon les résultats, cette plateforme peut contribuer à résoudre les défis les plus critiques de la communication véhicule-à-tout (V2X) en améliorant la sécurité et l’évolutivité.
In this paper, we present a private voting system that consists of N authorized voters who may vote to one of the K candidates or vote abstain. Each voter wants to compute the final tally while staying private and robust against malicious voters, who try to gain information about the vote of the other voters beyond the final result, or send incorrect information to affect the final tally. We design an information-theoretic private voting system based on Shamir secret sharing, which is secure and robust as long as there are up to (N-1)/3 malicious voters.
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There has been an unprecedented increase in the use of smart devices globally, together with novel forms of communication, computing, and control technologies that have paved the way for a new category of devices, known as high-end wearables. While massive deployments of these objects may improve the lives of people, unauthorized access to the said private equipment and its connectivity is potentially dangerous. Hence, communication enablers together with highly-secure human authentication mechanisms have to be designed. In addition, it is important to understand how human beings, as the primary users, interact with wearable devices on a day-to-day basis; usage should be comfortable, seamless, user-friendly, and mindful of urban dynamics. Usually the connectivity between wearables and the cloud is executed through the user’s more power independent gateway: this will usually be a smartphone, which may have potentially unreliable infrastructure connectivity. In response to these unique challenges, this thesis advocates for the adoption of direct, secure, proximity-based communication enablers enhanced with multi-factor authentication (hereafter refereed to MFA) that can integrate/interact with wearable technology. Their intelligent combination together with the connection establishment automation relying on the device/user social relations would allow to reliably grant or deny access in cases of both stable and intermittent connectivity to the trusted authority running in the cloud. The introduction will list the main communication paradigms, applications, conventional network architectures, and any relevant wearable-specific challenges. Next, the work examines the improved architecture and security enablers for clusterization between wearable gateways with a proximity-based communication as a baseline. Relying on this architecture, the author then elaborates on the social ties potentially overlaying the direct connectivity management in cases of both reliable and unreliable connection to the trusted cloud. The author discusses that social-aware cooperation and trust relations between users and/or the devices themselves are beneficial for the architecture under proposal. Next, the author introduces a protocol suite that enables temporary delegation of personal device use dependent on di�erent connectivity conditions to the cloud. After these discussions, the wearable technology is analyzed as a biometric and behavior data provider for enabling MFA. The conventional approaches of the authentication factor combination strategies are compared with the ‘intelligent’ method proposed further. The assessment finds significant advantages to the developed solution over existing ones. On the practical side, the performance evaluation of existing cryptographic primitives, as part of the experimental work, shows the possibility of developing the experimental methods further on modern wearable devices. In summary, the set of enablers developed here for wearable technology connectivity is aimed at enriching people’s everyday lives in a secure and usable way, in cases when communication to the cloud is not consistently available.
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Wireless traffic produced by modern mobile devices displays high temporal and spatial dynamics as users spontaneously engage in collective applications where a significant portion of generated data remains localized. As a result, conventional service provisioning approaches may no longer be sufficient in beyond fifth generation (B5G) systems. The challenge of increased dynamics on the access networks can be mitigated with moving cells. However, the deployment time of these temporary serving entities may lag behind the service demand lifetime. Another viable solution to offload excessive cellular traffic is to rely upon locally available radio resources offered by user devices via direct mmWave-based mesh interworking. An important challenge in such systems is related to the incentivization of users to partake in collaborative resource sharing. To leverage multi-hop mesh capabilities, we propose the use of emerging blockchain technology that offers cryptographically-strong accounting while maintaining the anonymity of the participants. With system-level evaluations, we demonstrate that the utilization of mobile blockchain methods allows for a non-incremental improvement in the offloading gains. This demonstrates the potential of the outlined proposal for becoming a successful mechanism in the emerging B5G systems.
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A vast digital ecosystem of entrepreneurship and exchange has sprung up with Bitcoin’s digital infrastructure at its core. We explore the worldwide spread of infrastructure necessary to maintain and grow Bitcoin as a system (Bitcoin nodes) and infrastructure enabling the use of bitcoins for everyday economic transactions (Bitcoin merchants). Specifically, we investigate the role of legal, criminal, financial, and social determinants of the adoption of Bitcoin infrastructure. We offer some support for the view that the adoption of cryptocurrency infrastructure is driven by perceived failings of traditional financial systems, in that the spread of Bitcoin infrastructure is associated with low trust in banks and the financial system among inhabitants of a region, and with the occurrence of country-level inflation crises. On the other hand, our findings also suggest that active support for Bitcoin is higher in locations with well-developed banking services. Finally, we find support for the view that bitcoin adoption is also partly driven by cryptocurrencies’ usefulness in engaging in illicit trade.
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Blockchain-based decentralized cryptocurrencies have drawn much attention and been widely-deployed in recent years. Bitcoin, the first application of blockchain, achieves great success and promotes more development in this field. However, Bitcoin encounters performance problems of low throughput and high transaction latency. Other cryptocurrencies based on proof-of-work also inherit the flaws, leading to more concerns about the scalability of blockchain. This paper attempts to cover the existing scaling solutions for blockchain and classify them by level. In addition, we make comparisons between different methods and list some potential directions for solving the scalability problem of blockchain.
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The smart factory is a representative element reshaping conventional computer-aided industry to data-driven smart industry while it is non-trivial to achieve cost effectiveness, reliability, mobility and scalability of smart industrial systems. Data-driven industrial systems mainly rely on sensory data collected from statically-deployed sensors. However, the spatial coverage of industrial sensor networks is constrained due to the high deployment and maintenance cost. Recently, mobile crowd sensing (MCS) has become a new sensing paradigm owing to its merits such as cost effectiveness, mobility and scalability. Nevertheless, traditional MCS systems are vulnerable to malicious attacks and single point of failure due to the centralized architecture. To this end, we integrate MCS with industrial systems without introducing any additional dedicated devices. To overcome the drawbacks of traditional MCS systems, we propose a blockchain-based MCS system (BMCS). In particular, we exploit miners to verify the sensory data and design a dynamic reward ranking incentive mechanism to mitigate the imbalance of multiple sensing tasks. Meanwhile, we also develop a sensory data quality detection scheme to identify and mitigate the data anomaly. We implement a prototype of BMCS on top of Ethereum and conduct extensive experiments on a realistic factory workroom. Both experimental results and security analysis demonstrate that BMCS can secure industrial systems and improve the system reliability.
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Smart contract technology is reshaping conventional industry and business processes. Being embedded in blockchains, smart contracts enable the contractual terms of an agreement to be enforced automatically without the intervention of a trusted third party. As a result, smart contracts can cut down administration and save services costs, improve the efficiency of business processes and reduce the risks. Although smart contracts are promising to drive the new wave of innovation in business processes, there are a number of challenges to be tackled. This paper presents a survey on smart contracts. We first introduce blockchains and smart contracts. We then present the challenges in smart contracts as well as recent technical advances. We also compare typical smart contract platforms and give a categorization of smart contract applications along with some representative examples.
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Compared with single cloud service providers, cloud exchange provides users with lower price and flexible options. However, conventional cloud exchange markets are suffering from a number of challenges such as central architecture being vulnerable to malicious attacks and cheating behaviours of third-party auctioneers. The recent advances in blockchain technologies bring the opportunities to overcome the limitations of cloud exchange. However, the integration of blockchain with cloud exchange is still in infancy and extensive research efforts are needed to tackle a number of research challenges. To bridge this gap, this paper presents an overview on using blockchain for cloud exchange. In particular, we first give an overview on cloud exchange. We then briefly survey blockchain technology and discuss the issues on using blockchain for cloud exchange in aspects of security, privacy, reputation systems and transaction management. Finally, we present the open research issues in this promising area.
In the Internet of Things (IoT), sensor networks form the basis for interactions with the environment and are seeing accelerated development. This chapter introduces the IoT challenges that we are going to examine here. These are challenges that are related to functioning, confidentiality and security. The chapter describes the concepts of authentication and integrity as well as the concepts of reputation and trust. It introduces the authors' contribution, the Blockchain Authentication and Trust Module (BATM) architecture. The chapter presents the notations used the general architecture of the BATM, and describes how BATM aims to respond to authentication needs by specifying the mechanisms that we have implemented. It explores the evaluation of BATM architecture through simulations. The chapter concludes the relevance of BATM with respect to the results obtained and also explains the possible future prospects of this work.
Blockchain technology can be extensively applied in diverse services, including online micro-payments, supply chain tracking, digital forensics, health-care record sharing, and insurance payments. Extending the technology to the Internet of things (IoT), we can obtain a verifiable and traceable IoT network. Emerging research in IoT applications exploits blockchain technology to record transaction data, optimize current system performance, or construct next-generation systems, which can provide additional security, automatic transaction management, decentralized platforms, offline-to-online data verification, and so on. In this article, we conduct a systematic survey of the key components of IoT blockchain and examine a number of popular blockchain applications. In particular, we first give an architecture overview of popular IoT-blockchain systems by analyzing their network structures and protocols. Then, we discuss variant consensus protocols for IoT blockchains, and make comparisons among different consensus algorithms. Finally, we analyze the traffic model for P2P and blockchain systems and provide several metrics. We also provide a suitable traffic model for IoT-blockchain systems to illustrate network traffic distribution.
Crowdsourced mesh networks are built, maintained and used by several participants that cooperate to provide and consume connectivity. Providers of infrastructure want to get compensation for their investments and earn tokens; users or consumers want the network to expand for improving the coverage of connectivity and stability. How do we collect funds from consumers and distribute them to providers, guaranteeing satisfaction of every participant? For that, we need of a system that coordinates the flow of economic value in mesh networks in a way that is not only transparent, automated, decentralized and secure, but also beneficial to all. We designed a new economic protocol called Fair to compensate providers for their investments. The key point of our model is that each provider will be paid with different prices for the forwarded traffic: the more devices a provider has, the higher its price/MB forwarded is, up to a certain limit. We implemented the model using MeshDApp, a local blockchain platform for mesh networks. Simulations show how our proposal ensures a win-win situation where the network grows and the providers are compensated for their investment. Also, continuous growth is incentivized while centralization due to few large providers controlling the network is avoided.