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Conditional Anonymity enabled Blockchain-based Ad Dissemination in Vehicular Ad-hoc Network (MS Thesis without Source Codes)

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Abstract and Figures

Data sharing is a fascinating in-vehicle service which provide multiple benefits to the vehicle users in the Vehicular Ad-hoc Networks (VANETs). One of the interesting in-vehicle services is advertisement sharing in VANETs which enable advertisers to market their products and services in the areas of the users interest. With the help of Blockchain (BC) technology, the vehicle users can also participate in the ads dissemination process to gain monetary incentives. However, the existing BC based VANET schemes suffer from privacy, security and efficiency issues. Zero Knowledge Proof of Knowledge (ZKPoK) and certificate-less cryptography are used in the existing schemes to enable fair incentive provision and privacy preservation. These schemes incur high computational cost on the resource constrained vehicles. Moreover, the lack of conditional anonymity in the existing schemes makes the system vulnerable to internal attacker scenario. Furthermore, VANETs require secure and efficient reputation verification mechanism to prevent replay attacks and reduce the storage cost. Additionally, the reliance on a centralized entity for the certificate revocation makes the system wide open to the single point of failure vulnerability. To overcome these issues, a BC based secure, efficient and conditional anonymity enabled scheme is proposed. Elliptic Curve Digital Signature based pseudonym update mechanism is employed to enable conditional anonymity and trace malicious vehicles. InterPlanetary File System is used to efficiently store the vehicles' reputation information and reduce the storage overhead. Moreover, the Shamir Secret Sharing algorithm is used to enable distributed revocation. Security analysis is performed to show that the proposed scheme is secure against multiple known attacks. The simulation results show the effectiveness and practicality of the proposed scheme.
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Conditional Anonymity enabled Blockchain-based
Ad Dissemination in Vehicular Ad-hoc Network
(MS Thesis without Source Codes)
By
Abid Jamal
CIIT/FA16-RIS-016/ISB
MS Thesis
in
Information Security
COMSATS University Islamabad, Islamabad - Pakistan
Spring, 2021
COMSATS University Islamabad
Conditional Anonymity Enabled Blockchain-based
Ad Dissemination In Vehicular Ad-hoc Network
A Thesis Presented to
COMSATS University Islamabad
In partial fulfillment
of the requirement for the degree of
MS (Information Security)
By
Abid Jamal
CIIT/FA16-RIS-016/ISB
Spring, 2021
ii
Conditional Anonymity Enabled Blockchain-based
Ad Dissemination In Vehicular Ad-hoc Network
A Post Graduate Thesis submitted to the Department of Computer Science as
partial fulfilment of the requirement for the award of Degree of MS (Information
Security).
Name Registration Number
Abid Jamal CIIT/FA16-RIS-016/ISB
Supervisor:
Dr. Mariam Akbar,
Assistant Professor, Department of Computer Science,
COMSATS University Islamabad,
Islamabad, Pakistan
Co-Supervisor:
Dr. Nadeem Javaid,
Associate Professor, Department of Computer Science,
COMSATS University Islamabad,
Islamabad, Pakistan
iii
Final Approval
This thesis titled
Conditional Anonymity Enabled Blockchain-based Ad
Dissemination In Vehicular Ad-hoc Network
By
Abid Jamal
CIIT/FA16-RIS-016/ISB
has been approved
For the COMSATS University Islamabad, Islamabad
External Examiner:
Prof. Dr. Muhammad Younus Javed,
Vice Chancellor,
Mirpur University of Science and Technology (MUST), Mirpur
Supervisor:
Dr. Mariam Akbar,
Assistant Professor, Department of Computer Science,
COMSATS University Islamabad, Islamabad
Co-Supervisor:
Dr. Nadeem Javaid,
Associate Professor, Department of Computer Science,
COMSATS University Islamabad, Islamabad
Head of Department:
Dr. Majid Iqbal,
Assistant Professor, Department of Computer Science,
COMSATS University Islamabad, Islamabad
iv
Declaration
IAbid Jamal (Registration No. CIIT/FA16-RIS-016/ISB) hereby declare that I
have produced the work presented in this thesis, during the scheduled period of
study. I also declare that I have not taken any material from any source except
referred to wherever due that amount of plagiarism is within acceptable range. If
a violation of HEC rules on research has occurred in this thesis, I shall be liable
to punishable action under the plagiarism rules of the HEC.
Date: July, 2021
Abid Jamal
CIIT/FA16-RIS-016/ISB
v
Certificate
It is certified that Abid Jamal (Registration No. CIIT/FA16-RIS-016/ISB) has
carried out all the work related to this thesis under my supervision at the De-
partment of Computer Science, COMSATS University, Islamabad and the work
fulfils the requirement for award of MS degree.
Date: July, 2021
Supervisor:
Dr. Mariam Akbar,
Assistant Professor, Department of
Computer Science
Co-Supervisor:
Dr. Nadeem Javaid,
Associate Professor, Department of
Computer Science
Head of Department:
Dr. Majid Iqbal,
Department of Computer Science
vi
DEDICATION
Dedicated
to my mentor Dr. Nadeem Javaid and loving Parents, who
equipped me with pearls of knowledge and showed me the way of
spiritual and personal enlightenment in this world and the world
hereafter.
vii
ACKNOWLEDGEMENT
First of all, thanks to Allah Almighty who give me strength and confidence to
complete this dissertation. After that, I would like to express my profound appre-
ciation to many people who supported me during my MS and who helped me to
complete my thesis. Their generous support made this research work possible
Firstly, I would like to express my sincere gratitude to my advisor Dr. Nadeem
Javaid for the continuous support of my MS study and related research, for his
patience, motivation and immense knowledge. His guidance helped me in all the
time of research and writing of this thesis. I could not have imagined having a
better advisor and mentor for my MS study. I am truly indebted to him for his
knowledge, thoughts and friendship.
I would like to thank my parents for their continuous support, understanding and
assistance whenever I needed them throughout my MS studies and research work.
Furthermore, I would like to thank my brothers Mohammad Jamal, Ahmed Jamal
and Qasim Jamal. I believe that without their motivation, it is not possible to
succeed throughout my life. I am always grateful to them for their encouragement
and support.
Last but not the least, I am greatly thankful to Director of ComSens Lab and all
of my colleagues at CUI for providing me the warm and friendly atmosphere.
viii
ABSTRACT
Conditional Anonymity enabled Blockchain-based Ad
Dissemination in Vehicular Ad-hoc Network
Data sharing is a fascinating in-vehicle service which provide multiple benefits
to the vehicle users in the Vehicular Ad-hoc Networks (VANETs). One of the
interesting in-vehicle services is advertisement sharing in VANETs which enable
advertisers to market their products and services in the areas of the users interest.
With the help of Blockchain (BC) technology, the vehicle users can also partici-
pate in the ads dissemination process to gain monetary incentives. However, the
existing BC based VANET schemes suffer from privacy, security and efficiency
issues. Zero Knowledge Proof of Knowledge (ZKPoK) and certificate-less cryp-
tography are used in the existing schemes to enable fair incentive provision and
privacy preservation. These schemes incur high computational cost on the resource
constrained vehicles. Moreover, the lack of conditional anonymity in the existing
schemes makes the system vulnerable to internal attacker scenario. Furthermore,
VANETs require secure and efficient reputation verification mechanism to prevent
replay attacks and reduce the storage cost. Additionally, the reliance on a cen-
tralized entity for the certificate revocation makes the system wide open to the
single point of failure vulnerability. To overcome these issues, a BC based secure,
efficient and conditional anonymity enabled scheme is proposed. Elliptic Curve
Digital Signature based pseudonym update mechanism is employed to enable con-
ditional anonymity and trace malicious vehicles. InterPlanetary File System is
used to efficiently store the vehicles’ reputation information and reduce the stor-
age overhead. Moreover, the Shamir Secret Sharing algorithm is used to enable
distributed revocation. Security analysis is performed to show that the proposed
scheme is secure against multiple known attacks. The simulation results show the
effectiveness and practicality of the proposed scheme.
ix
Conference Proceedings
1Abid Jamal, Sana Amjad, Usman Aziz, Muhammad Usman Gurmani,
Saba Awan and Nadeem Javaid, “A Privacy Preserving Hybrid Blockchain
based Announcement Scheme for Vehicular Energy Network”, In Confer-
ence on Complex, Intelligent, and Software Intensive Systems, pp. 142-151.
Springer, Cham, 2021. Download
2Abid Jamal, Muhammad Usman Gurmani, Saba Awan, Maimoona Bint
E Sajid, Sana Amjad and Nadeem Javaid, “Blockchain enabled Secure and
Efficient Reputation Management for Vehicular Energy Network”, In Confer-
ence on Complex, Intelligent, and Software Intensive Systems, pp. 406-416.
Springer, Cham, 2021. Download
3 Javed, Muhammad Umar, Abid Jamal, Nadeem Javaid, Noman Haider,
and Muhammad Imran. “Conditional Anonymity enabled Blockchain-based
Ad Dissemination in Vehicular Ad-hoc Network” In 2020 International Wire-
less Communications and Mobile Computing (IWCMC), pp. 2149-2153.
IEEE, 2020. Download
4 Shahid, Affaf, Umair Sarfraz, Muhammad Waseem Malik, Muhammad So-
haib Iftikhar, Abid Jamal and Nadeem Javaid, “Blockchain-Based Reputa-
tion System in Agri-Food Supply Chain”, Advanced Information Networking
and Applications. AINA 2020. Advances in Intelligent Systems and Com-
puting, vol 1151. Springer, 2020. Download
5 Khan, Asad Ullah, Affaf Shahid, Fatima Tariq, Abdul Ghaffar, Abid Jamal,
Shahid Abbas and Nadeem Javaid, “Enhanced Decentralized Management
of Patient-Driven Interoperability Based on Blockchain”, In International
Conference on Broadband and Wireless Computing, Communication and
Applications, pp. 815-827. Springer, Cham, 2019. Download
x
TABLE OF CONTENTS
Dedication vii
Acknowledgements viii
Abstract ix
Conference Proceedings 81
List of Figures xiv
List of Tables xv
List of Algorithms xvi
List of Symbols xvii
1 Introduction 1
1.1 Introduction ............................... 2
1.1.1 Background and motivation .................. 3
1.1.2 Blockchain ............................ 4
1.1.3 Thesis contributions ...................... 5
1.1.4 Organization of thesis ..................... 6
2 Literature review and problem statement 7
2.1 Literature review ............................ 8
2.2 Problem Statement ........................... 13
2.2.1 Subproblem: 1 ......................... 13
2.2.2 Subproblem: 2 ......................... 13
3 Proposed system models and methodologies 15
3.1 System model: 1 ............................ 16
3.2 Proposed scheme 1 ........................... 16
3.2.1 System Initialization ...................... 16
3.2.2 Registration ........................... 16
xi
3.2.3 Ad Publication ......................... 17
3.2.4 Ad Dissemination ........................ 18
3.2.4.1 Broadcast Message .................. 18
3.2.4.2 Response Message .................. 18
3.2.5 Ad Credibility Check ...................... 18
3.2.6 Proof Verification ........................ 18
3.2.7 Reward Payment ........................ 19
3.2.7.1 Batch Verification .................. 19
3.2.8 Design Goals .......................... 19
3.2.8.1 Conditional Anonymity ............... 19
3.2.8.2 Untraceability ..................... 19
3.2.8.3 Certificate Revocation and Transparency . . . . . . 19
3.2.8.4 Credible Ad Dissemination ............. 20
3.3 System model: 2 ............................ 20
3.3.0.1 Certificate Authority ................. 20
3.3.0.2 Road Side Units ................... 20
3.3.0.3 Vehicles ........................ 21
3.3.0.4 Blockchain ...................... 22
3.3.0.5 Smart Contract .................... 22
3.3.0.6 InterPlanetary File System ............. 22
3.4 Proposed Scheme 2 ........................... 22
3.4.1 System Initialization ...................... 22
3.4.2 Registration ........................... 23
3.4.3 Vehicle Trading ......................... 23
3.4.4 Reputation Calculation ..................... 24
3.4.5 Distributed Revocation ..................... 24
3.4.6 Data Storage .......................... 26
4 Simulation results and discussions 27
4.1 Conditional Anonymity enabled Ad dissemination in Vehicular Ad-
hoc Network ............................... 28
4.2 Blockchain enabled Secure and Efficient Reputation Management
for Vehicular Energy Network ..................... 30
4.2.1 Computation Overhead ..................... 32
4.2.2 Communication Overhead ................... 35
4.2.3 Storage Overhead ........................ 36
4.3 Security Analysis ............................ 37
4.3.1 Replay Attacks Prevention ................... 37
xii
4.3.2 Conditional Privacy Preservation ............... 38
4.3.3 51% Attack ........................... 38
4.3.4 Smart Contract Analysis .................... 40
5 Conclusion and future work 41
5.1 Conclusion ................................ 42
5.2 Future work ............................... 42
6 References 43
Appendices 53
.A Detail of Appendices .......................... 54
.B Implementation of proposed solution 1: ................ 55
.B.1 Smart contract code for proposed solution: 1 ......... 64
.C Implementation of proposed solution 2: ................ 67
.C.1 Smart contract code for proposed solution 2 ......... 79
Conference Proceedings 81
xiii
List of Figures
3.1 Ad dissemination in BC based VANET ................ 17
3.2 Secure and efficient reputation management in VEN ......... 21
4.1 Off-chain Computations ........................ 28
4.2 On-chain Computations ........................ 29
4.3 Batch verification results ........................ 30
4.4 ECDSA and Group Key execution time comparison ......... 32
4.5 Frequency of key updates ECDSA vs Group Key ........... 32
4.6 Shamir Secret Sharing results ..................... 33
4.7 Malicious vehicle detection using time delay ............. 34
4.8 Probability of 51% attack ....................... 35
4.9 BC vs IPFS execution time ...................... 36
4.10 BC vs IPFS storage cost ........................ 37
4.11 Transaction age in replay attack .................... 38
4.12 Transaction age when using IPFS ................... 39
4.13 Oyente analysis of smart contract ................... 40
xiv
List of Tables
4.1 Mapping Table for System Model 1 .................. 29
4.2 Mapping Table for System Model 2 .................. 31
4.3 Gas Cost of Smart Contract Functions ................ 34
4.4 Communication Overhead ....................... 35
xv
List of Algorithms
1 Reputation Calculation ......................... 25
2 Distributed Revocation ......................... 25
3 Shamir Secret Sharing .......................... 26
xvi
List of Abbreviations and Symbols
BC Blockchain
RSU RoadSide Unit
ITS Intelligent Transport System
MANET Mobile Ad-hoc Network
V2V Vehicle to Vehicle
V2I Vehicle to Infrastructure
OBU On-Board Unit
DSRC Dedicated Short-Range Communication
SPoF Single Point of Failure
DLT Distributed Ledger Technology
ECC Elliptic Curve Cryptography
P2P Peer to Peer
CA Certificate Authority
ECDSA Elliptic Curve Digital Signature Algorithm
PoAR Proof of Ad Receiving
CF Cuckoo Filter
IPFS Interplanetary Filesystem
SSS Shamir Secret Sharing
VsAd sender vehicle
VrAd receiving vehicle
GGenerator of elliptic group
hNumber of Ad fragments
P K Public Key
P R Private Key (Secret Key)
Sig Digital Signature
Cert Pseudonym Certificate
Link Linkability between RID and PID
MAd message
T I deadline (Time Threshold)
xvii
MSK Master Secret Key
M P K Master Public Key
RevK ey Revocation Key
RID Real Identity
P I D Pseudonym Identity
ts Timestamp
T xReq Request Transaction
tThreshold
nNumber of Shamir secret shares
V, V eh Vehicle
req() Request
Enc() Encryption Function
xviii
Chapter 1
Introduction
1
Chapter 1 Introduction
1.1 Introduction
Vehicular Ad-hoc Networks (VANETs) have introduced a communication standard
for Intelligent Transport Systems (ITS). It enable the vehicles to communicate
with each other and with the infrastructure to share important information. The
communication in a vehicular network can be used for enabling multiple fascinat-
ing applications. Different types of data can be broadcast in vehicular networks
like important alert messages, road/weather conditions, commercial information,
etc. Sharing such information can significantly improve the travel experience of
individuals. Multiple in-vehicle services can be enabled in VANETs like data
trading, data sharing, entertainment, and e-commerce to extend the capabilities
of traditional VANETs. In this regard, one of the fascinating in-vehicle services
is vehicular advertising. Vehicular advertising is a low-cost and efficient service
to promote a product or service in a vehicular network. It is beneficial for both
the advertiser and the users. Advertisers can market their products or service to
their potential customers in a specific area to gain high profits. In this way, users
can receive ads that are more relevant to their surroundings. Because in-vehicle
advertising can enable advertisers to target their potential customers in a specific
area and users can receive more relevant ads. In vehicular networks, advertis-
ing companies can provide incentives to Roadside Units (RSUs) to use them as
intermediaries to broadcast their ads to all of the vehicles in its communication
range. To disseminate these ads to a larger audience, the advertisers can stimu-
late the end-users by providing monetary incentives. Most of the existing vehicular
ad dissemination schemes depend upon a central authority for its operations and
management. This can make the system prone to single point of failure and DDoS
attacks. To overcome the issues that may occur in centralized systems, researchers
have focused on using decentralized approaches.
Recently many of the Blockchain (BC) based vehicular schemes [1,2,3] are pro-
posed. These schemes effectively manage the traffic conditions in highly populated
urban areas to deal with different types of issues. In addition, BC based vehicular
networks also enables energy trading, information sharing, load balancing, etc.
[4,5,6]. Vehicles in a VANETs are equipped with an On-Board Unit (OBU) that
uses Dedicated Short-Range Communications (DSRC) protocol to communicate
with the other vehicles to share advertisements, trade energy, and broadcast an-
nouncement messages in the network. However, since the conventional VANETs
rely on a centralized server for the network management, it is prone to multiple
shortcomings; including, Single Point of Failure (SPoF), limited scalability and
2Thesis by: Abid Jamal
Chapter 1 Introduction
different security vulnerabilities.
In this section of thesis, the background and motivation, introduction of blockchain,
contributions and organization of thesis have been presented.
1.1.1 Background and motivation
BC technology is widely used in vehicular networks due to its prominent fea-
tures, like transparency, data integrity, availability, tamper-proof records, etc.,
[7,8,9,10,11]. Researches have been conducted in order to devise schemes that
can provide fair incentives and preserve the privacy of vehicles [12]-[28]. Despite
the several benefits, the BC based VANETs are prone to some issues; like pri-
vacy leakage, storage overhead, ineffective vehicle reputation management, and
centralized revocation, etc.
In [29] authors proposed a BC-based ad dissemination scheme in VANETs. In
this scheme, the advertisers pay RSUs to disseminate their ads in the area of in-
terest. The RSU publishes the ad to all the vehicles in its communication range
and motivate them to disseminate it to the vehicles that are not in the commu-
nication range of RSU by providing incentives. The authors addressed issues of
privacy leakage and dishonest incentive gains. They use Zero-Knowledge Proof
of Knowledge (ZKPoK) and certificate-less cryptography to hide the identities of
the vehicles involved in ad dissemination and prevent malicious vehicles from un-
fairly obtaining incentives. In their proposed system, the vehicles use ZKPoK for
registration to prove their identity without sharing any private information. In
this way, even the registration authority does not know the real identity of the
vehicles. The use of ZKPoK can enable anonymity and conditional linkability to
preserve privacy and prevent double claim attacks. However, ZKPoK can allow
internal attackers to misuse their anonymity to share malicious ads in the network.
And as the vehicles are registered using certificate-less cryptography, the authen-
ticated malicious vehicle (internal attacker) cannot be identified. Besides, every
ad dissemination instance will require the vehicles to generate ZKPoK to verify
the ad is indeed received or disseminated, which can put excessive computational
overhead. Also, there is a requirement of the message credibility technique so that
the vehicles that are not in the communication range of RSU, can verify whether
the ad/message that is coming from an authenticated vehicle is indeed credible.
Furthermore, the vehicles in VANET verify the trustworthiness of their trading
partners to prevent monetary loss. The scheme introduced in [30] uses transaction
3Thesis by: Abid Jamal
Chapter 1 Introduction
indexes to verify the trustworthiness of the vehicles. However, this scheme is prone
to replay attacks since the malicious vehicles can utilize older transaction indexes
to appear reliable. Another important aspect of vehicular networks is privacy
preservation. Authors in [31] use One Time Addresses (OTA) and [32] use Group
signatures to achieve vehicles’ privacy. However, due to lack of vehicle traceability
mechanism, the malicious vehicles can share false information without getting
caught. Additionally, the existing schemes suffer from the high cost of storing BC
ledgers. To reduce the storage cost, the scheme proposed in [32] stores BC ledger
data on selective edge stations. Nevertheless, this scheme is vulnerable to data
loss when the edge stations’ security is compromised. In the existing BC based
vehicle reputation schemes [33,9], a centralized CA is used for revoking the digital
certificate of malicious vehicles. This approach makes the system centralized and
makes the system prone to a single point of failure.
1.1.2 Blockchain
BC, a well-known distributed ledger, is the integration of the distributed system
and the cryptography. In BC, a copy of the ledger is shared among all the mem-
bers of a peer-to-peer network. Tamper-resistance, immutability, no single point
of failure, elimination of the third party are the core features of the BC. Bitcoin
is a first successful use case which was first proposed by Satoshi Nakamoto in
his whitepaper [34]. A block in BC has two components, a block header, and
a block body. Block header contains a nonce value, previous block hash, times-
tamp, and the Merkle root. And the block body contains the transaction records.
Despite its wide adoption, its use case was limited to digital currency. Over the
years, researchers explored this technology and developed new frameworks with
more functionalities e.g. Ethereum [35], Iota [36], Hyperledger [37]. Due to this,
use cases of BC go beyond cryptocurrencies such as supply chain, food industry,
health, IoT, VANETS, etc [38] - [41]. Despite the increase in use cases and the
advents of new BC frameworks, one main concern is to design a consensus pro-
tocol having low computation and communication overheads. The consensus in
distributed systems plays a vital role to achieve a consistent view of the shared
ledger. The reason is that any member node may try to interrupt the reputation of
the ledger by proposing block having conflicted transaction e.g. double-spending.
To deal with this issue, PoW was designed in Bitcoin which is a strong consensus
algorithm. However, the member needs to solve complex mathematical puzzles
which are computationally expensive. In Etheruem [42], PoS was utilized which is
computationally less expensive as compared to PoW. Proof of Authority (PoA) is
4Thesis by: Abid Jamal
Chapter 1 Introduction
a relatively new consensus algorithm that is gaining popularity because members
of the BC network can achieve consensus without increasing computational power
and having high stakes in ether.
1.1.3 Thesis contributions
In our proposed work, we employ Elliptic Curve Digital Signature (ECDSA) based
pseudonym update mechanism to efficiently preserve the privacy of the vehicles.
The pseudonyms of the vehicles are continuosly updated to prevent vehicle tracking
and stalking. Conditional anonymity is enabled by storing a linkability between
the real identity (RID) and the pseudo identity (PID) at the CA. Hence, the mali-
cious vehicles can be traced. Bayesian Inference is used for verify the credibility of
the advertisement message and avoid internal attacks. Batch verification mecha-
nism is employed to efficiently verify multiple signed messages simultaneously. An
effective reputation verification mechanism is used to securely store the vehicles’
trustworthiness scores and prevent replay attacks. Shamir Secret Sharing (SSS)
algorithm is used to enable distributed revocation to prevent SPoF. Moreover, In-
terPlanetary File System (IPFS) is used for reducing the storage cost and ensuring
persistent data availability. The list of our contributions is as follows:
ECDSA based pseudonym update mechanism is used for vehicle registration
to reduce computational cost and enable conditional anonymity,
Bayesian inference model is used to overcome the dissemination of misleading
ads by internal attackers. Since the pseudonym identities are linked with the
original identities, the malicious users can be identified and reported to the
trusted authorities for the certificate revocation,
batch verification mechanism is employed to efficiently verify aggregated
proofs,
an effective vehicle reputation verification mechanism is proposed in which
the vehicles’ ratings are securely stored to prevent replay attacks.
SSS algorithm is used to enable distributed revocation.
IPFS is used for ensuring persistent data availability and efficient data stor-
age.
and finally, performance analysis is done to evaluate the efficiency of our
proposed system. We have implemented our proposed scheme in Python and
5Thesis by: Abid Jamal
Chapter 1 Introduction
Solidity and evaluated the time cost of the communications and transactions
that occur in the network.
1.1.4 Organization of thesis
The remainder of the thesis is organized as follows: related studies are presented in
Chapter 2. System model and proposed methodology are demonstrated in Chapter
3. Chapter 4describes the simulation results of our proposed schemes. Finally,
the findings of this work along with future directions are presented in Chapter 5.
6Thesis by: Abid Jamal
Chapter 2
Literature review and problem statement
7
Chapter 2 Literature review and problem statement
2.1 Literature review
In recent years, many BC-based solutions have been proposed for vehicular net-
works to address the mobility effects on efficiency of BC in VANETs. Authors in
[12] analyzed the effects on mobility on BC based vehicular networks and evaluated
the performances on parameters like stability of rendezvous, successful blocks ad-
dition and number of blocks that can be exchanged during rendezvous. However,
they only addressed those issues in vehicle to infrastructure context and did not
focus on V2V communication in the network. Authors in [29] focused on fairness
of incentive provision while preserving privacy of vehicles during ad dissemination
in VANETs. However, the proposed scheme lacks ad-verification mechanism to
prevent dissemination of fake ads by internal attackers. The authors did not pro-
vide any mechanism to prevent flooding attacks. This can occur due to lack of
prioritization scheme and ad-restriction mechanism which can suppress important
alert messages in the pool of unnecessary ads. Also the authors did not provide
any mechanism to stimulate the ad receivers to respond to the ad sender, which
can prevent honest nodes from obtaining their legit incentive. In [13] and [14],
authors proposed BC-enabled privacy preserving mechanism for data sharing and
resource sharing respectively. Consortium BC was used to mitigate security and
privacy issues in the network. Authors in [13] used Three Weight Subjective Logic
(TWSL) to develop reputation management scheme to help in choosing authentic
data source whereas authors in [16] used logistic regression method to calculate
the trust value of nodes.
Authors in [15] enabled conditional privacy in BC based carpooling scheme by
using Private Proximity test with location tags. However, the proposed scheme
used cloud server for data storage which can act as single point of failure while
handling enormous amount of requests from vehicular nodes. Several researchers
[24],[28] and [16] have focused on evaluation of credibility/correctness of messages
that are disseminated in vehicular network. In this regard, authors in [24] used
Bayesian Inference Model for generating message ratings. Parameter used for
message credibility are, distance between message sender and event location. In
[28], the trust related data of node and message is stored in local BC. Vehicles
confirm the validity of received message by querying the local BC which contains
all of the trust values. This scheme provides accurate results because it uses
Proof of Work (PoW) consensus mechanism. However, this scheme is not efficient
because PoW is a resource intensive consensus mechanism and querying BC ledger
for validation of every message can cause significant delays. The authors in [16]
8Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
used logistic regression method for calculating reputation values which helps in
identifying and removing malicious vehicles from the network. The reputation
values are evaluated by two metrics: direct trust, which is based on historical
behavior of the vehicle and indirect trust, which is based on a recommendations
from the witnesses. Similarly, the authors in [17], [18], and [19] also worked on
enabling conditional privacy in VANETs.
BC prevents data tampering and enables immutability due to its inherent decen-
tralized nature. However, researcher have found some of the vulnerabilities which
may disrupt the BC based networks [43]-[59]. The authors in [43] enabled BC based
collaborative crowdsensing in autonomous vehicles. In [44] the authors analyzed
the effects of mobility on the blocks propagation in a BC based vehicular network.
Furthermore, in [45] and [46], authors proposed BC and SDN enabled solutions
to enable secure communications in IoV networks. Similarly, multiple security
related solutions are proposed in [47]-[53] for different types of vehicular networks.
In [54], the authors address the issue of security vulnerabilities in smart vehicles.
They exploit a permissioned BC based reputation scheme to prevent false infor-
mation dissemination in the network. However, their proposed reputation scheme
does not allow the less reputed vehicles to regain their reputation values. In [55],
authors propose One-Time Password and Artificial Intelligence based reputation
mechanism in vehicular edge computing to enable secure data sharing. A secure
BC based incentive scheme is proposed in [56] for traffic event validation. In this
scheme, the reputation of vehicles is calculated based on their past events and
consortium BC is utilized for storing the vehicles’ reputation values. The authors
in [57] address the issue of malicious service provision in vehicular cloud network.
They propose a BC based trust management scheme by utilizing three-valued sub-
jective logic to identify the malicious service providers. The authors in [58] address
the issue of computationally intensive reputation and consensus mechanism in ve-
hicular energy network. They propose Proof of Work based reputation scheme to
reduce the mining cost. The authors in [59] propose a BC based energy and data
trading scheme. Their proposed scheme uses smart contracts to handle trading
disputes and data redundancy.
Enabling trusted communication in vehicular networks is one of the important
issue in BC based vehicular networks. In this regard, several researchers have pro-
posed different solutions related to authentication and reputation management in
vehicular networks to prevent malicious access [60]-[68]. The authors in [60] and
9Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
[61] propose BC based authentication schemes for vehicular edge computing net-
works. Moreover, in [62] and [63], authors enabled trusted communication in un-
manned aerial vehicles network. Furthermore, the authors in [64] enabled trusted
access in vehicular networks. In [65] provided efficient authentication scheme for
vehicular social networks, whereas, [66] provided a reputation management scheme
for secure authentication. The authors in [67] propose a BC based scheme to store
and manage the authentication information of the vehicles. Moreover, they utilize
vehicular edge computing to reduce the computational and storage cost. The au-
thors in [68] address the issue of false information sharing in the network. They
propose a BC based decentralized trust management system to record the vehicle
reputation based on their network participation rate.
The authors in [69] propose a BC based data storage system to overcome the
overwhelming cost of uploading data on the BC. They use smart contracts to
reduce the size of re-uploaded data and exploit data partitioning mechanism to
decrease the computational overhead. They also adjusted the difficulty of Proof
of Work consensus algorithm to enhance the system efficiency in terms of data
updates. In [70], authors address the issue of high computational and storage cost
in BC based vehicular message dissemination. They propose a consortium BC
enabled edge computing system to reduce the communication cost and storage
requirement. Similar work is proposed by authors in [71]-[74].
Due to open nature of the BC based vehicular networks, it is necessary to detect
and revoke the malicious vehicles from the network. In this regard, the authors in
[33] propose a BC enabled efficient certificate revocation list management scheme.
Their proposed pseudonym shuffling mechanism reduces the storage cost of large
number of pseudonyms. In [75], the authors utilize BC based edge computing
for efficient vehicles’ trust data calculation and storage. However, their proposed
scheme is vulnerable to private information leakage due to transparency feature
of BC. In [76], the propose a BC based distributed authentication scheme. How-
ever, their proposed scheme is susceptible to single point of failure as the users’
authentication information is stored in a centralized cloud server. In [31], the au-
thors propose a distributed pseudonym identity management mechanism to utilize
self-generated vehicle certificates in BC based vehicular networks. However, their
proposed scheme does not support vehicle traceability, which can lead to false
information dissemination and fraudulent transactions.
Also, similar work is done by authors in [77] - [91]. The authors in [77] proposed
a price and load forecasting scheme for big data in smart cities. They utilized
10 Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
Deep Long Short-Term Memory (LSTM) to perform short and medium term load
and price forecasting. Furthermore, in [78] a Demand Side Management (DSM)
scheme is proposed for efficient energy management and trading in smart grids.
They utilized two heuristics algorithms namely, Cuckoo Search Algorithm and
Strawberry Algorithm to optimize electricity cost and reduce Peak-to-Average
Ratio (PAR). The simulation results show that their proposed scheme effectively
reduces PAR and electricity costs. With the combination of Demand Response
(DR) and renewable energy, different scheduling algorithms for residential DR
under Real-Time Pricing (RTP)-based pricing conditions are proposed in [79].
According to demand, users and appliances are categorized, and user preferences
and electricity costs are formulated as optimization problems. Based on extensive
simulations, their proposed algorithms are evaluated for their effectiveness. It is
concluded that Renewable Energy Sources (RES) have been useful in reducing the
cost of total electricity as compared with grid-only power. Furthermore, in [80],
a BC based data sharing scheme is proposed that also enables access control in
IoT devices. Their proposed scheme effectively overcomes the authentication and
trust issues which occur during data dissemination between IoT devices. Their
proposed scheme is compared with the state-of-the-art schemes in terms of smart
contract gas consumption. Moreover, the authors in [81] provided an overview
of Load Management (LM) techniques in smart grids, including dynamic pricing
based Direct Load Control (DLCs) and Energy Consumption Scheduling (ECSs)
based on incentives. Additionally, they also discussed the challenges related to LM
related technologies and smart grids. Authors in [82], proposed a meta-heuristic
based Home Energy Management System (HEMS) by incorporating Enhanced
Differential Evolution (EDE) and harmony search algorithm (HSA). Additionally,
a hybrid of HSA and EDE is developed to optimize the energy consumption. The
simulation results of their proposed scheme show that it efficiently reduces cost
and PAR. Authors in [83] proposed a hybrid Grey Wolf Differential Evolution
Optimization (GWDEO) technique to optimize the PAR and cost in smart grids.
Their proposed scheme is considering two pricing schemes, namely, RTP and CPP.
However, in their proposed scheme there is trade off between electricity cost and
user comfort. In [84], authors proposed a hybrid of Genetic Algorithm (GA) and
Particle Swarm Optimization (PSO) optimization technique named GAPSO for
residential electricity load scheduling in smart grids. Their proposed scheme ef-
ficiently reduces the electricity cost and users’ discomfort by utilizing Multiple
Knapsack Problem (MKP). Authors in [85] proposed a priority based DSM tech-
nique for HEMS to enable load optimization in smart homes. They developed
11 Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
an Evolutionary Accretive Comfort Algorithm (EACA) that allows time vary-
ing priorities to be measured in time and device-based features. Their proposed
EACA generates an optimal energy consumption pattern which maximizes user
comfort and reduces the electricity cost. In [86], authors developed an Energy
Management Model (EMM) for near Zero Energy Buildings (nZEBs) based on
GA, Teaching Learning Based Optimization (TLBO), EDE and Enhanced Differ-
ential Teaching Learning Algorithm (EDLTA). Their proposed scheme efficiently
decreases the electricity, carbon emissions and maximizes the user comfort. Their
proposed scheme integrates RES and improves the performance of the system in
terms of PAR and carbon emission reduction. Authors in [87] proposed a hy-
brid technique for DSM based on EDE and TLBO schemes. In this technique,
the electricity cost is measured by using Day-ahead real time pricing (DA-RTP)
and CPP. Their proposed scheme is evaluated using simulations and results which
shows the efficiency of the system in terms of electricity cost, PAR, and waiting
time reduction. In [88], a hybrid of TLBO and GA is developed for optimizing
the electricity and user comfort considering the electricity prices are announced
on day-ahead basis. Authors in [89] propose an EMM scheme to optimize energy
consumption in the residential area to reduce the PAR and electricity cost while
maximizing user comfort. To reduce electricity costs, the proposed EMM scheme
utilizes Mixed Integer Linear Programming (MILP) to optimally schedule smart
appliances and EV charging/discharging.
In [90], authors propose a BC based agricultural food supply chain solution to
overcome the issues of traceability, accountability, and security in the similar ex-
isting schemes. In this scheme, BC and IPFS are utilized to store the information
about each step of the supply chain cycle to enable trust, traceability, and credibil-
ity of the entities. The simulations and results show that their proposed scheme is
efficient and scalable due to low computational and storage cost. In [91], authors
propose a data sharing scheme based on BC and IPFS to mitigate the issues of
trust, transparency, security in smart grids. The authors enabled authentication
by utilizing RSA signatures to prevent the penetration of malicious vehicles in
the network. Also, an incentive mechanism is developed to encourage the users
to provide reviews about the data they receive from their peers. Furthermore,
Watson analyzer is utilized to detect fake user reviews. Similarly, some authors
developed trust schemes for vehicular networks by combining BC and AI [92]-[96].
In [92], authors propose AI enabled trust management scheme for BC based ve-
hicular networks. Moreover, in [93], [94], and [95], deep learning methods are used
for enabling trusted communication. Furthermore, [96] enables secure and trusted
12 Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
task offloading in vehicular edge computing by exploiting Stackelberg game and
Double Auction schemes.
2.2 Problem Statement
Based on the limitations found in the literature review, a problem statement is
formulated. The problem statement is divided into two subproblems.
2.2.1 Subproblem: 1
In [29], certificate-less cryptography is employed which allows vehicle to register in
the network without providing private information to the registration authority.
Due to which, internal attackers cannot be punished even if their malicious behav-
ior is identified in the network because the registration authority does not possess
the real identities of the vehicles. Also, in this scheme, vehicles use ZKPoK to
enable anonymous communication. However, the anonymity provided by ZKPoK
can be misused by internal attackers to disseminate misleading ads in the network
without payment. ZKPoK is a secure but computationally expensive protocol. Ve-
hicles need to generate ZKPoK for every message exchange in the network which
can cause unnecessary computational overhead. Furthermore, the RSU individ-
ually verifies every Proof of Ad Receiving (PoAR) sent by vehicles (for obtain-
ing rewards). This is an inefficient approach as it can cause long delays when a
large number of PoARs are needed to be verified. Moreover, in [14], a reputation
mechanism was utilized to validate the trustworthiness of vehicles. However, no
mechanism was used to check the credibility of the messages that are being sent
by vehicles which can allow the spread of malicious messages in the network.
2.2.2 Subproblem: 2
In [30], authors have proposed a BC based location privacy preservation scheme.
In their proposed scheme, the trustworthiness of the vehicles is ensured by re-
quiring them to share the transaction index which holds their reputation values.
However, this allows the malicious vehicles to share an older transaction index
which contains their previous reputation value, thus making them appear trust-
worthy. In [32], a BC-enabled privacy preserving scheme is proposed for vehicular
social network. They use an incentive/punishment mechanism to identify mali-
cious users. However, their proposed incentive/punishment scheme is ineffective
in preventing the spread of false information in network. Furthermore, their pro-
posed BC construction stores selective BC data on edge stations to overcome data
13 Thesis by: Abid Jamal
Chapter 2 Literature review and problem statement
redundancy. However, their scheme is susceptible to data loss even when a small
number of edge stations get compromised. Moreover, since vehicular networks
have high mobility, their proposed group key scheme suffers from high storage and
computation overheads due to frequent key updates. In [31], the authors propose
a pseudonym management framework for vehicular network. However, since a new
pseudo-ID is generated for each transaction, their proposed scheme is unable to
trace malicious vehicles. Moreover, the authors in [33,9] propose a BC based key
management schemes to efficiently distribute the vehicle registration and revoca-
tion information in vehicular network. However, in their proposed schemes, the
certificate revocation process is performed by a central entity which is prone to
SPoF.
14 Thesis by: Abid Jamal
Chapter 3
Proposed system models and methodologies
15
Chapter 3 Proposed system models and methodologies
3.1 System model: 1
To demonstrate an ad dissemination scenario, we consider two vehicles namely
Sender Vehicle VSand Receiver Vehicle VR, CA, RSU and Advertiser to overcome
the problems mentioned in 2.2.1. Vehicles request MA for digital certificate by
providing its private information. MA orders CA to generate digital certificate
(PID) for the vehicle, then creates an encrypted linkability between the PID and
RID of the vehicle. This linkability is encrypted with the secret key of MA. The
vehicles use the pseudonym for dissemination of ads in a private manner. As
the pseudonym is updated after a certain time threshold, it prevents malicious
vehicles to trace any specific vehicle by its behaviour. The proposed system model
is depicted in Fig. 3.1. The implementation of the system model 1 is given in
Appendix .B Further details of about each phase of our proposed scheme are
given below.
3.2 Proposed scheme 1
3.2.1 System Initialization
Elliptic Curve Cryptography is used to generate key pairs for CA and MA. First,
the CA and MA generates their private keys P RCA and P RM A. Then they com-
pute their public keys P KCA =P RCA xGand P KMA =P RM A xG. These keys
are used to encrypt the communication between the authorities and encrypting
the linkability between the original identity and the pseudonym of the vehicle.
3.2.2 Registration
In registration phase, the advertiser and vehicles request MA for digital certifi-
cate. The MA verifies the private information of the entity and then forwards the
request to CA. In case of advertiser, the registration is done by providing public
P Uadv and private key P Radv. However, the vehicles are registered by providing
private information PVto MA. When the digital certificate (pseudonym) CertVis
generated by CA, the MA generates an encrypted linkability between the CertV
and PVas such Link(PV||CertV)P RM A . This linkability is used to expose the real
identity of the malicious vehicles in case of disputes.
16 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
Transaction
Ad Dissemination
Chain
Advertiser
Ad
Ad dissemination
Certificate Revocation
Request
Fraudulent
activity
Revoke
Certificate
Certificate
Issuance/Revocation
Chain
Monitoring
Authority
Smart Contract Transaction
Ad Dissemination
Blockchain
Ad Publication
Roadside Unit
Advertisement
Proof of Ad Receiving
Certificate
Authority
Figure 3.1: Ad dissemination in BC based VANET
3.2.3 Ad Publication
The advertiser generates a Merkle Root of the ad that it intends to promote in the
network. Then it creates a smart contract with RSU in its region of interest. The
advertiser deposits a reward amount in the smart contract with some pre-defined
conditions (h, T I, sigadv ), where his the number of fragments, T I is the deadline,
sigadv is the signature of advertiser. These parameters guides the ad disseminating
vehicles in generating the proof.
17 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
3.2.4 Ad Dissemination
After the advertiser deposits the amount in the smart contract, the RSU broadcasts
the ad (M) to all of the vehicles in its vicinity and encourage them with the
monetary rewards to disseminate further in the network. The vehicle generate
two types of messages to ensure successful dissemination of the ads.
3.2.4.1 Broadcast Message
The VSinitiates a broadcast message to all of the vehicles that are not in the range
of RSU with reward motivation and then expects to receive a PoAR from the Ad
Receiver vehicle to ensure successful ad dissemination.
3.2.4.2 Response Message
The VRgenerate PoAR of the ad message and calculates the Merkle root . Then
it signs the PoAR and sends it back to the Ad Sender vehicle.
3.2.5 Ad Credibility Check
When a vehicle receives an ad, it checks for the message validity by using a prob-
abilistic algorithm called Bayesian Inference Model [24] before responding to the
VS. If the ad is found to be a misleading one, the VSis reported to the MA and
its digital certificate is revoked. Bayesian Inference model follows Bayes’ theorem
in which the probability of the vehicles future behavior (posterior probability)
is calculated based on the previous behavior of the vehicle (prior probability).
Following is the Bayes’ equation: P(H|E) = P(E|H).P(H) / P(E), where the
P(H|E) is the posterior probability of an event occurrence, P(E|H) is the like-
lihood of an event occurrence, P(E) is the marginal likelihood and P(H) is the
prior probability of an event occurrence.
3.2.6 Proof Verification
After the VRreceives the M, it will be divided into hfragments. Then randomly
fragments are signed by the VRand sent back to the VSand RSU as a proof that
it has indeed received the ad. This proof is checked against the Merkle Root of
the original ad at RSU. If the proof is found to be authentic, it is forwarded to
the smart contract for reward payment phase. Otherwise, the vehicle is considered
malicious and its certificate is revoked.
18 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
3.2.7 Reward Payment
The RSU aggregates multiple PoAR together that are transacted by VSand verifies
their authenticity against Merkle root of ad in smart contract by using batch
verification mechanism. If it is proven valid, then the RSU, VS, and VRare given
incentive. Otherwise, the transaction is rejected. The batch verification helps in
improving the efficiency of the system because individual verification of ads can
introduce unnecessary delays.
3.2.7.1 Batch Verification
For batch verification, the proofs received by vehicles are aggregated together as
one batch. Then these proves are verified against the Merkle root of the original
ad. Divide-and-Conquer mechanism is used for batch verification, in which the
batch is divided into smaller batches at every failed verification attempt. In this
way, the malicious vehicles can be identified easily and their digital certificates are
revoked in an efficient manner.
3.2.8 Design Goals
3.2.8.1 Conditional Anonymity
The vehicles privacy should be preserved so that the malicious users so that can-
not reveal their real identities and simultaneously the trusted authorities should
have access to their private information so that in case of disputes, they can be
identified.
3.2.8.2 Untraceability
The pseudonym identity of the vehicle should be untraceable. In order to achieve
this property, the pseudonyms are updated after a predefined time threshold so
that the vehicles cannot be traced by their behaviour in the network.
3.2.8.3 Certificate Revocation and Transparency
When a vehicle is identified as malicious, its certificate should be revoked in order
to prevent further dissemination of fake ads by it. The certificate revocation list
should be public so that other vehicles can avoid communicating with the identified
malicious vehicle.
19 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
3.2.8.4 Credible Ad Dissemination
Ads that are being disseminated in the network, should be verified by the ad
receiver before providing PoAR. In this way, if any vehicle tries to disseminate
misleading ads in the network, it should be detected and reported to the authori-
ties.
3.3 System model: 2
This work enables a secure and efficient reputation management for BC based
vehicular networks. This system model is developed for problem statement 2.2.2
and consists of six phases, as shown in Figure 3.2. The implementation of system
model 2 is given in .C.
The system’s cryptographic parameters are set in the first phase, which is called
system initialization phase. In the second phase, registration of the vehicles is
performed via CA. For registration purpose, the identity information of the vehicles
is used. In the third phase, vehicles perform secure trading using the verified
trustworthiness of the vehicles. In the fourth phase, the reputation values of the
vehicles are calculated on the bases of their behavior and the ratings provided by
the neighboring vehicles. The fifth phase is the distributed revocation phase. In
this phase, SSS algorithm is used to enable distributed revocation. To save storage
space, Road Side Units (RSUs) upload users’ reputation data on IPFS in the sixth
phase, which is termed as the data storage phase. Figure 3.2 also shows the lists of
identified limitations and proposed solutions. The former are labeled from L1 to
L6 while the latter are labeled from S1 to S5. The details of the entities involved
in the proposed system model are given below.
3.3.0.1 Certificate Authority
The registration of vehicles and RSUs is handled by a trusted central entity, known
as CA. In the proposed scheme, an encrypted copy of the mapping between the
real ID RID and the pseudo ID P I D of the vehicles is stored in CA. It is done in
order to ensure vehicles’ traceability.
3.3.0.2 Road Side Units
In the proposed scheme, RSUs perform multiple operations. In order to facili-
tate secure trading between the vehicles, RSUs assist the vehicles retrieve repu-
tation data from BC and IPFS. Also, the BC ledger which contains the vehicles’
20 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
Registration
R_keys1,s2,s3
Reputationcalculation
Rep_ListVeh.rep > 0.3
s1 s2 s3
RevokeR_Key(CRB) RevList VehRatings
V2VTrading
IPFS_addr(Rep_list,RevList)
Distributed Revocation
DistributedStorage
Certificate Authority
LimitationsIdentiied
L1: Replay attacks
L2: False Information dissemination
L3: Data loss due to substandard storage
L4: Inefficient privacy scheme
L5; Lack of malicious vehicle traceability
L6: Centralized revocation mechanism
ProposedSolutions
S1: IPFS
S2: Malicious vehicle detection
S3: Pseudonym update mechanism
S4; Conditional privacy
S5: Distributed revocation
L1,L3S1
L6S5
L2S2
L4,L5S3,S4
RoadSide Unit
Registration
Reputation Storage
Revocation
Blockchain
IPFS
Trading
CRBVeh.rep < 0.3
Mapping
Figure 3.2: Secure and efficient reputation management in VEN
reputation data is stored on RSUs. Hence, RSUs also enable data availability,
immutability, and transparency.
3.3.0.3 Vehicles
In the proposed scheme, the vehicles share information about road conditions
with each other and with the RSUs to prevent traffic jams and other unpleasant
situations. Additionally, the vehicles engage in data and energy trades with each
21 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
other for the purpose of increasing their reputation values and earning monetary
gains.
3.3.0.4 Blockchain
In the proposed scheme, Ethereum BC is used in conjunction with IPFS to store
the reputation scores of the vehicles in a decentralized manner. BC prevents SPoF
while enabling data transparency, integrity and availability. Because BC has a
block size limit, the complete reputation data of all vehicles cannot be stored in a
single block. Thus, to avoid this, IPFS is used to store reputation data of vehicles
and the hash address corresponding to those data are stored on BC.
3.3.0.5 Smart Contract
In the proposed scheme, the RSUs use smart contracts to upload the reputation
data to the IPFS and store the corresponding hash value on BC. Furthermore,
vehicles use smart contracts to obtain reputation data of their trading partners
from RSUs.
3.3.0.6 InterPlanetary File System
IPFS is a distributed storage framework that ensures long term data availability
and easy accessibility. In the proposed framework, the IPFS is used to store
the reputation data of the vehicles. To improve the efficiency of the system, the
reputation data is uploaded to IPFS in form of a batch of 100 vehicles. The IPFS
returns a fix sized SHA-256 hash address for each corresponding batch. This hash
address is then stored on the BC to ensure transparency.
3.4 Proposed Scheme 2
Detailed description of each phase involved in the proposed model is provided in
this section. The following are some of the notations used in the scheme. V1and
V2are two trading vehicles. RID and P I D, on the other hand, are the vehicles’
real and pseudo identities, respectively.
3.4.1 System Initialization
For system’s initialization, an Elliptic curve y2=x3+ax+b mod p is selected. Here
a,bZ
p, and pis large prime number. gis the generator of the elliptic group.
After that, the CA generates its cryptographic material by selecting a master
22 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
private key CAM SK and generating a master public key CAM P K =CAM S K ×g.
CA uses ECDSA for signing the digital certificates. The signing key and verifying
key of CA are CAsigKey and C Av erK ey , respectively.
CA also generates the revocation key Revkey, which is used for revoking mali-
cious vehicles from the network. To enable distributed revocation, we use the
SSS algorithm. This algorithm divides the Revkey into nnumber of secret shares
(s1,s2,s3,...sn,). Each RSU is provided with one secret share. A threshold tis
defined as the number of shares required to recover the Revkey . After every suc-
cessful revocation, the CA updates the Revkey to prevent malicious usage of the
outdated Revkey
3.4.2 Registration
V1sends its private information over a secure channel to the CA and requests
for its P I DV1. To determine whether the vehicle is malicious or not, the CA
first checks the RIDV1of a vehicle in both the current users’ list and the CRL.
The CA creates P I DV1for a vehicle after its verification is completed. The CA
generates and encrypts the mapping created between RIDV1and P I DV1, with
EncC AM P K . The mapping, given as Map(P I DV1)= EncC AM P K (RI DV1||P I DV1),
ensures conditional privacy.
3.4.3 Vehicle Trading
After registration, the vehicles become a part of the network and trade energy
with other members of the network. The steps involved in the trading process are
provided below.
V1sends a trading request T xReq = (r eq, ts, P I DV1, SigV1sigK ey ) to V2. Here
req,ts and Sig represent the requested data, timestamp and the digital
signature, respectively.
After receiving the T xReq, the reputation value of V1is checked by V2by
requesting a nearest RSU.
The RSU retrieves the reputation value of V1from IPFS using the hash
stored in BC and sends it to V2.
V2responds to V1if the reputation value of V1is above 0.5. Otherwise, it
rejects the request.
23 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
After trading, the vehicles provide ratings about each other to the RSU.
These ratings are used for calculating the reputation value of the vehicles.
3.4.4 Reputation Calculation
In this phase, the reputation values of the vehicles are calculated based upon the
ratings provided by their trading partners. The vehicles provide positive or neg-
ative ratings to each other depending upon their satisfaction regarding the trade.
The reputation value of a vehicle ranges from 0 to 1. The initial reputation value
of a vehicle is set to be 0.5. Each positive rating increases the reputation value
by 0.01 while each negative rating decreases the reputation value by 0.03. The
negative rating value is greater than positive rating value so as to stop the vehicles
from acting negatively. When the vehicles maintain a rating above 0.7, they re-
ceive monetary incentives. Moreover, when the reputation value of a vehicle drops
below 0.3, it is considered as malicious. The reputation calculation mechanism is
given in Algorithm 1. The digital certificates of the malicious vehicles are revoked
by using the proposed SSS based distribution revocation mechanism as discussed
in Section 3.4.5 and given in Algorithm 2. The sequential revocation of vehicles
inflicts high computational overhead, which leads to scalability issue. Hence, the
pseudonyms of the malicious vehicles are added to Certificate Revocation Batch
(CRB) to collectively revoke the pseudonym certificates of multiple malicious ve-
hicles. The revocation process takes place after a predefined time threshold (30
minutes in our model) to prevent malicious vehicles from staying in the network.
The workflow of SSS is given in Algorithm 3.
3.4.5 Distributed Revocation
In this phase, SSS algorithm is used for revoking digital certificates of malicious
vehicles in a distributed manner. Here RSUinit refers to the RSU that initiates the
revocation process. The workflow of distributed revocation is presented below.
When a CRB of 10 vehicles is formed, the RSUinit initiates the revocation
request.
The RSUinit requests other RSUs to provide their secret share for recovering
the Revkey .
The Revkey is recovered after receiving nnumber of secret shares (s1,s2,s3,...)
from other RSUs.
24 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
Algorithm 1: Reputation Calculation
Result: CRB, Updated Reputation Values
function giveRatings(V, TRUE/FALSE)
if TradeSatisfaction==TRUE then
if V eh.rep >= 0.7then
giveIncentive(V);
else
V eh.rep =V eh.rep + 0.01;
end
else
if V eh.rep < 0.3then
AddToCRB(V);
else
V eh.rep =V eh.rep - 0.03;
end
end
Add Updated Reputation Values Data to IPFS;
Store I P F SH ash on BC;
Algorithm 2: Distributed Revocation
Result: RevokedList, RevKey, updatedRevK ey
function getSecretShares()
if t >= 30 minutes then
RSUinit sends Req to all RSUs to get nnumber of secret shares
(s1,s2,..sn,);
if n >=th then
RSUinit reconstructs Revkey using Algorithm 3;
else
print(insufficient number of secret shares);
end
else
function Revoke(CRB,Revkey )
Revoke the vehicles in CRB using Revkey ;
Add revoked vehicles’ P I Ds to RevList;
Upload RevList to IPFS;
Store I P F SH ash on BC;
Request CA to update the Revkey ;
end
The ID of RSUinit, the Revkey and the CRB are added to the BC after
successful revocation. Adding this data to BC ensures transparency of the
revocation process.
Each Revkey is only used once to prevent malicious behavior. Hence, the
RSUinit requests the CA for updating the Revkey .
25 Thesis by: Abid Jamal
Chapter 3 Proposed system models and methodologies
Algorithm 3: Shamir Secret Sharing
Result: nnumber of secret shares
function generateSecretShares(Revkey ,n,th)
// Revkey is divided into nsecret shares;
// th is set as threshold;
// return nsecret shares;
function ReconstructSecret(n,th)
Secret shares are requested from RSUs;
if receivedShares >=th then
Successfully reconstruct Revkey ;
return Revkey ;
else
return “Insufficient number of secret shares”;
end
3.4.6 Data Storage
In the proposed scheme, the vehicles’ reputation data is stored on IPFS and the
corresponding hash address is stored on BC. The reason for using this approach is
to reduce storage cost and prevent replay attacks. We identified the issue of replay
attack in [30], wherein, the malicious vehicles can prove their trustworthiness using
old T xI Ds to show the outdated reputation value. Hence, to overcome that, the
vehicles in the proposed system are restricted to only use the reputation data
stored in the latest block. Since, it is not possible to store the complete record
of the vehicles’ reputation data in a each block due to block size limit, IPFS is
utilized to store the reputation data and BC is used to store the corresponding
hashes.
26 Thesis by: Abid Jamal
Chapter 4
Simulation results and discussions
27
Chapter 4 Simulation results and discussions
4.1 Conditional Anonymity enabled Ad dissem-
ination in Vehicular Ad-hoc Network
This section describes the results of sub-problem 2 which is presented in sec-
tion 2.2.1. We implemented our scheme using Python and Solidity Language. In
Python language, we implemented a vehicular network scenario in which advertis-
ers, RSU and vehicles interact with each other. We used web3.py to connect our
Python code with smart contracts. In order to inspect the performance of the pro-
posed scheme, six different phases namely Registration, Pseudonym update, Ad
publication, Ad Broadcast, Ad Response, and Reward Payment are considered for
analysis. Figure 4.1 gives the computation time for the above-mentioned phases.
It is evident from the results that registration phase takes a little longer than
other phases. But as the registration is required only once per vehicle, it does not
too much to the time complexity of the system. Figure 4.2 shows the time taken
by on-chain computations that occur during smart contract execution. Overall,
the time taken by our proposed scheme falls under a practical and efficient range
which is suitable for highly mobile vehicular network.
Figure 4.1: Off-chain Computations
28 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Figure 4.2: On-chain Computations
Limitations Solutions Validation
L1: ZKPoK based
authentication
scheme is used
which is computa-
tionally expensive
S1: To reduce the cost
of authentication, vehicles
are registered using ECDSA
based pseudonym mecha-
nism is used
V1: Figure 4.1 shows the
time taken by the ECDSA
based registration
L2: Lack of mes-
sage credibility
technique
S2: Message credibility is
calculated based on the dis-
tance of the vehicle from the
area of interest
V2: No, direct validation
is performed. However, the
results in figure 4.1 shows
the time taken by ad dis-
semination operation which
also includes the message
credibility time.
L3: Delays caused
by sequential mes-
sage verification
S3: Batch verification
mechanism is used to re-
duce the time taken by
signature verification of
multiple messages
V3: Figure 4.3 shows the
comparison between sin-
gle message verification and
batch verification of 10 mes-
sages
Table 4.1: Mapping Table for System Model 1
29 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Single Verification Batch Verification
0
2000
4000
6000
8000
10000
12000
14000
16000
Time ( s)
Figure 4.3: Batch verification results
4.2 Blockchain enabled Secure and Efficient Rep-
utation Management for Vehicular Energy
Network
This section describes the results of sub-problem 2 which is presented in section
2.2.2. We have used Ganache to create a local BC instance and the official IPFS
software. The results are divided into three subsections mentioned below.
30 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Limitations Solutions Validation
L1: Replay attacks
due to sharing older
transaction indexes
S1: IPFS based replay at-
tacks prevention
V1: The replay attacks are
detected by checking the
age of the transactions as
shown in Figure 4.11 and
4.12
L2: False infor-
mation dissemina-
tion due to ineffec-
tive incentive/pun-
ishment scheme
S2: Malicious vehicle de-
tection mechanism based on
the ratings provided by the
neighboring vehicles
V2: Figure 4.7 shows the
time taken by different ve-
hicles. Benign vehicles re-
spond more quickly as com-
pared to the malicious ones.
L3: Data loss due
to selective storage
of BC ledger
S3: The data is stored on
the IPFS to reduce the stor-
age overhead of the BC
ledger. Only the IPFS hash
is stored on the BC ledger.
Hence, it can be stored on
all the RSU nodes.
V3: Figure 4.10 shows the
storage space overhead of
IPFS vs BC. Figure 4.9
shows the execution time
of BC vs IPFS. Figure 4.8
shows the probability of
51% attack w.r.t to number
of benign nodes.
L4: The OTA
and group sig-
nature schemes
are inefficient in
performance
S4: ECDSA based
pseudonym mechanism
is used. The pseudonyms
are frequently updated to
prevent linkage attacks.
Figure 4.4 shows the perfor-
mance comparison between
the proposed ECDSA and
other schemes. Figure 4.5
shows the frequency of key
updates in group signatures
vs ECDSA.
L5: Lack of mali-
cious vehicle trace-
ability
S5: Conditional anonymity
is enabled by creating a
mapping between the real
identity and the pseudonym
identity
V5: No, direct validation.
However, the performance
of the privacy preservation
scheme is evaluated in Fig-
ure 4.4
L6: Centralized re-
vocation
S6: Shamir secret shar-
ing based distributed revo-
cation
V6: Figure 4.6 shows the
time taken by the SSS op-
erations.
Table 4.2: Mapping Table for System Model 2
31 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
4.2.1 Computation Overhead
Keygen VerifySign
Time (ms)
Group Sig
OTA
ECDSA
0
1
2
3
4
5
6
7
Figure 4.4: ECDSA and Group Key execution time comparison
Figure 4.5: Frequency of key updates ECDSA vs Group Key
OTA [32], Group Signature [32] and the proposed ECDSA based pseudonym
scheme are compared in Figure 4.4. Due to the usage of Kerl hashing algorithms,
it is apparent that the OTA scheme generate keys much more slowly than other
systems. In order to prevent the private keys leakage, the OTA scheme uses each
32 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Secret shares generation Secret reconstruction
0.0
0.1
0.2
0.3
0.4
0.5
0.6
Time (Secs)
Figure 4.6: Shamir Secret Sharing results
address only once. Moreover, it falls short of handling the high speed requirement
of vehicles in a vehicular network due to high computational cost. The figure also
shows the time taken by group signature scheme for generating keys. It takes
slightly more time as compared to the proposed pseudonym scheme due to the
number of interactions between multiple nodes required for generating the group
key.
Figure 4.5 shows the number of key updates required in group key generation and
ECDSA pseudonym generation methods. It is evident from the figure that in the
group key method, the key needs to be updated more frequently as compared
to the ECDSA method. It occurs because the vehicles frequently visit different
locations and form different groups to preserve their privacy. On the other hand,
in the proposed ECDSA method, the pseudonyms are updated at a predefined
interval. Hence, it incurs less computational cost.
The vehicle request and response time delays are depicted in Figure 4.7. The
vehicles contact the nearby vehicles for cooperation, trade or information sharing.
Prior to engaging in a trade, the vehicles exchange their reputation scores with each
other to enable trust. From the results, it is observed that when the vehicle share
the authentic reputation information with its peer, the response time generally
follow a same trend. However, when a vehicle shares fake reputation information,
33 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
1 2 3 4 5 6 7 8
0
1
2
3
4
5
6
7
Requests and Responses
Time (ms)
Figure 4.7: Malicious vehicle detection using time delay
it takes a little longer than the authentic response like the 7th request in figure 4.7.
Hence, we have used the delay in response time to identify the malicious vehicle.
Function Transaction Cost (gas) Execution Cost (gas)
Constructor Call 563320 385624
Add User 103873 82409
Increase Reputation 34599 12943
Decrease Reputation 29360 7704
Get User Reputation 22973 1509
Table 4.3: Gas Cost of Smart Contract Functions
Table 4.3 shows the gas cost of different operations involved in the smart con-
tract in the proposed scheme. The cost is given in terms of transaction cost and
execution cost. It is measured in gas, which is a unit defined by the Ethereum
foundation. The constructor call operation requires the highest transaction and
execution cost. It is because the constructor call involves the execution of the
complete smart contract. The cost of executing the complete smart contract is
much more than executing individual functions.
Figure 4.9 shows the comparison between BC and IPFS in terms of time required to
store and retrieve data. It is evident from the figure that IPFS requires significantly
less time compared to BC. Hence, using IPFS for storing the data is considered
as an optimal solution for the proposed scheme.
34 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
050 100 150 200
0.00
0.05
0.10
0.15
0.20
0.25
Probability of 51% attack
benign nodes = 8
benign nodes = 11
benign nodes = 14
benign nodes = 17
benign nodes = 20
Computational resources of attackers
Figure 4.8: Probability of 51% attack
4.2.2 Communication Overhead
Phase Procedure Cost
Registration Vehicle registration request to CA 443 (Bytes)
CA response to Vehicle 440 (Bytes)
V2V Trading V1 sends trading request to V2 245 (Bytes)
V2 requests rep(V1) from RSU 232 (Bytes)
RSU responds to V2 80 (Bytes)
V2 responds to V1 260 (Bytes)
Data Storage RSU sends storage request to IPFS 1 (MB)
IPFS returns the hash to RSU 32 (KB)
Table 4.4: Communication Overhead
Table 4.4 shows the communication overhead of the proposed scheme. It is divided
into three phases: registration, vehicle trading and data storage. The registration
phase includes the vehicle requesting the pseudonym certificate from the CA and
CA returning the pseudonym certificate to the vehicle. The vehicle trading phase
includes the vehicle sending trading request to another vehicle and requesting
reputation values from the RSU. The data storage phase includes the RSU sending
the encrypted reputation data to IPFS and receiving a fixed sized hash value from
35 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Store
Time (ms)
Retrieval
0
2
4
6
8
Blockchain
IPFS
Figure 4.9: BC vs IPFS execution time
IPFS. The data storage phase is the only costly phase of the proposed scheme as
it requires sending 1 MB sized data to IPFS.
4.2.3 Storage Overhead
Figure 4.10 shows the cost of storing actual data on BC compared with cost of
storing the IPFS hash address of the data. It is quite evident the cost of storing
actual data on BC rises almost exponentially, whereas storing the hash value
requires only few bytes. The reason is that in BC based vehicular networks, a
complete copy of BC ledger is needed to be stored on every RSU node. Since,
the vehicles’ reputation data is updated regularly, it incurs high storage cost on
the overall system. To overcome the storage issue, the authors in [31] proposed
a scheme, wherein they stored the BC ledger on selective RSUs. However, their
scheme introduces the issue of data unavailability and increased communication
cost due to high number of data retrieval requests. Hence, to reduce the storage
cost of BC, we use IPFS to store the actual data and its hash address on the BC.
The content address which is returned by the IPFS, is a fix sized SHA-256 hash
value irrespective of the size of the data. Hence it is an efficient approach to store
the IPFS hash address on BC instead of the actual data.
36 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Number of batches
Actual Data
IPFS Hashes
0
0
1
1
2
2
1e6
Size (bytes)
3456789
Figure 4.10: BC vs IPFS storage cost
4.3 Security Analysis
In this section, the security analysis of the proposed scheme is presented.
4.3.1 Replay Attacks Prevention
Replay attack is a type of a passive attack in which outdated legitimate information
is reused to deceive the users. The vehicle reputation scores are stored in IPFS
and the hash values are stored in BC for trustworthiness verification in VENs. It
is ideal to store and retrieve the reputation scores of vehicles from the latest block.
However, due to the block size limit and exponential increase in the consumption
cost, the reputation scores of all vehicles can not be stored in a single block. In
[30], the reputation score of each vehicle is stored as a single transaction on BC and
the trustworthiness of a vehicle is verified using T xID . However, this approach
allows malicious vehicles to send outdated T xIDs to appear trustworthy. The
replay attack in the existing scheme is detected using the transaction age, which is
calculated by comparing the transaction timestamp with the current time. Figure
4.11 shows the transaction age of different transactions. It is observed that the age
of most of the transactions is above the pre-defined time threshold, which indicates
37 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
that the transactions are outdated. To overcome this issue, the reputation scores
of the vehicles are stored in IPFS. Figure 4.12 shows the transaction age when
IPFS is used for storing the reputation scores. It is observed from the figure that
the transaction age is lower than the threshold. It is because the vehicles use only
the latest block for retrieving the transaction scores.
0231 46
58
79
0
25
50
75
100
125
150
175
Transaction age (secs)
Transactions
tim e t h reshold
Figure 4.11: Transaction age in replay attack
4.3.2 Conditional Privacy Preservation
In the proposed scheme, the pseudonym certificates are used for hiding the real
identity of the users. The real identity information of the vehicle is stored by
the CA so that in case of disputes, the true identity of the malicious vehicles can
be exposed. In [31], authors have used OTA method to prevent privacy leakage
that occurs due to data linkage. However, their proposed OTA scheme lacks
traceability feature, hence the malicious vehicles cannot be identified or removed
from the network.
4.3.3 51% Attack
One of the commonly known vulnerabilities of BC networks is the 51% attack.
It occurs when an attacker gains control of more than 50% of the BC network.
This attack is generally easy to perform in small BC networks where there are
less number of benign miners. We take this attack into consideration because
38 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
0 2 3 5
14 6 79
8
0
20
40
60
80
10 0
12 0
140
Transaction Age (secs)
Transactions
tim e t h r esh old
Figure 4.12: Transaction age when using IPFS
some BC based VENs [32] tend to reduce the number of benign miners to lessen
the data redundancy and storage overhead of multiple miner nodes. However,
this approach increases the probability of 51% attack since the number of benign
miners is inversely proportional to the probability of 51% attack as depicted in
Figure 4.8. We use the following equation to calculate the probability of 51%
attack.
P rob(51%) = hashRate(Malicious)
hashRate(All)(4.1)
To overcome the storage issue while maintaining a high number of benign nodes
in a BC based VEN, we use IPFS for data storage. In this way, the BC ledger can
be stored on all benign miner nodes while reducing the storage cost. To overcome
the 51% attack, we use a private BC and a proof of authority consensus algorithm.
In the private BC, the mining process is performed only by the authorized miners,
thereby, reducing the probability of the attack.
39 Thesis by: Abid Jamal
Chapter 4 Simulation results and discussions
Figure 4.13: Oyente analysis of smart contract
4.3.4 Smart Contract Analysis
For the security analysis of our smart contract, we use the open-source Oyente
tool. It is a widely used smart contract security analysis tool, which aids in iden-
tifying the well-known vulnerabilities in the smart contracts [59,98]. Figure 4.13
shows the security analysis results of the smart contract used in the proposed work
against the vulnerabilities. Some of the eminent smart contract vulnerabilities
are Integer Underflow/Overflow, Parity Multisig Bug 2, Re-Entrancy Vulnerabil-
ity, Callstack Depth Attack Vulnerability, Transaction-Ordering Dependence and
Timestamp Dependency. It is evident from the figure that the analysis results
return “False” for all of the attacks, which implies that the smart contract used
in our proposed scheme is secure against these attacks.
40 Thesis by: Abid Jamal
Chapter 5
Conclusion and future work
41
Chapter 5 Conclusion and future work
5.1 Conclusion
In this thesis, we have analyzed issues related to security, computational overhead
and conditional privacy in existing vehicular ad dissemination schemes. We have
proposed a BC-based ad dissemination scheme that enables conditional anonymity
by using pseudonyms instead of ZKPoK, as well as efficient proof verification by
using batch verification. The proposed scheme reduces computational cost and
enables malicious vehicle detection. Also the vehicle tracing attacks are mitigated
by updating the pseudonyms of vehicles after a regular interval. Furthermore, a
BC based reputation management system is proposed to promote efficient repu-
tation sharing in VENs. The proposed system initiates with the registration of
vehicles through the usage of real and pseudo identities. The registration is done
via CA, which also maps the P ID s of the vehicles with their RIDs. The P I Ds
are generated with the help of ECDSA, which ensures conditional anonymity and
traceability. In the underlying system, distributed revocation is ensured via SSS
algorithm. Moreover, the storage overhead is reduced using IPFS. The reputa-
tion data is stored in IPFS while the hashes generated by IPFS are stored in BC.
Simulations are performed and the results show the efficacy of the proposed sys-
tem in terms of computational cost and storage overhead. 18-20% reduction in
computational overhead and 35-40% reduction in storage overhead are observed
when using the proposed system. In the end, the security analysis on the bases
of replay attack, 51% attack and smart contract vulnerabilities prove the model’s
robustness.
5.2 Future work
In future, we will further improve the performance of our proposed scheme by
employing Cuckoo Filters and IOTA Tangle DLT. Moreover, we will develop a
mechanism to reuse the pseudonyms that are previously revoked in order to reduce
the storage overhead on RSUs.
42 Thesis by: Abid Jamal
Chapter 6
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1Abid Jamal, Sana Amjad, Usman Aziz, Muhammad Usman Gurmani,
Saba Awan and Nadeem Javaid, “A Privacy Preserving Hybrid Blockchain
based Announcement Scheme for Vehicular Energy Network”, In Confer-
ence on Complex, Intelligent, and Software Intensive Systems, pp. 142-151.
Springer, Cham, 2021. Download
2Abid Jamal, Muhammad Usman Gurmani, Saba Awan, Maimoona Bint
E Sajid, Sana Amjad and Nadeem Javaid, “Blockchain enabled Secure and
Efficient Reputation Management for Vehicular Energy Network”, In Confer-
ence on Complex, Intelligent, and Software Intensive Systems, pp. 406-416.
Springer, Cham, 2021. Download
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53 Thesis by: Abid Jamal
Research Proposal
Full-text available
In this work, an encyclopedic study of the blockchain based energy trading, data trading and sharing, and incentive mechanisms, used in various fields of life like energy, finance, business, data trading, healthcare, etc., is presented. The study critically analyzes different survey papers and ranks them using a recency score. This work also presents major blockchain related future research perspectives, which provide solid working directions to the research community. The use of blockchain technology with the Electric Vehicles (EVs) is also discussed to tackle different issues related to existing systems, such as privacy, security, lack of trust, etc., and to promote transparency, data immutability and tamper proof nature. Moreover, in this study, a new and improved charging strategy, termed as Mobile vehicle-to-Vehicle (M2V) charging strategy, is used to charge the EVs. It is further compared with conventional Vehicle-to-Vehicle (V2V) and Grid-to-Vehicle (G2V) charging strategies to prove its efficacy. In the proposed work, the charging of vehicles is done in a Peer-to-Peer (P2P) manner to remove the intermediary parties and deal with the issues related to them. Moreover, to store the data related to traffic, roads and weather conditions, a Transport System Information Unit (TSIU) is used, which helps in reducing road congestion and minimizing road side accidents. In TSIU, the data is stored in InterPlanetary File System (IPFS). Furthermore, mathematical formulation of the total charging cost, the shortest distance between EVs and charging entities, time taken to traverse the shortest distance and to charge the vehicles is done using real time data of EVs. The phenomena of range anxiety and coordination at the crossroads are also dealt with in the study. Moving ahead, edge service providers (edge nodes) are introduced to ensure efficient service provisioning. A caching system is also introduced at the edge nodes to store frequently used services. The power flow and the related energy losses for G2V, V2V and M2V charging strategies are also discussed in this work. In addition, an incentive provisioning mechanism is proposed on the basis of timely delivery of credible messages, which further promotes users’ participation. To check the robustness of the proposed model, an attacker model is designed and tested against different attacks including selfish mining attack. In future, the proposed model robustness will be tested against more attacks. To prove the efficiency of the proposed work, simulations will be performed. Moreover, the security analysis of the proposed work will also be done using Oyente.
Conference Paper
Full-text available
The vehicular announcement is an essential component of the Intelligent Transport System that enables vehicles to share important road information to reduce road congestion, traffic incidents, and environmental pollution. Due to the multiple security issues like single point of failure, data tampering, and false information dissemination, many researchers have proposed Blockchain (BC) based solutions to ensure data correctness and transparency in the vehicular networks. However, these schemes suffer from high computational cost and storage overhead due to the use of unsuitable BC on the vehicular layer, costly au-thentication schemes, and inefficient digital signature verification methods. Moreover, the privacy leakage can occur due to publicly available reputation values and lack of pseudonyms update mechanism. In this paper, we propose a privacy-preserving hybrid BC based vehicular announcement scheme to enable secure and efficient announcement dissemination. We use IOTA Tangle to enable the benefits of BC on vehicular layer while reducing the storage and computational cost. We employ Elliptic Curve Cryptography based pseudonym update mechanism for hiding the real identities of vehicles. To prevent false information dissemination in the network, we propose a reputation-based incentive mechanism for encouraging the users to provide honest ratings about the announcement messages. Furthermore, we use Cuckoo Filter to enable lightweight trustworthiness verification of the vehicles without revealing their reputation values. We also employ a batch verification mechanism to reduce the delays caused by digital signature verification. Moreover, we use InterPlanetary File System, and Ethereum BC for ensuring data availability and secure trust management.
Article
Full-text available
The rapid growth and technological progressions in the vehicle edge computing and networks (VECON) enhanced existing vehicular administrations through information sharing and information investigation, which further incremented traffic security difficulties. This carries the need to verify vehicle networks with gigantic information stockpiling substances. Recognizing the vehicles that communicate fashioned messages and ensuring the protection of every vehicle is an essential assignment. Blockchain can be utilized as an effective solution to provide security during vehicle edge computing. Every transaction and data is recorded in the blockchain, which expands the number of blocks after some time. Another test in blockchain methods is utilizing a consensus mechanism, which can be effectively undermined by the attackers. Artificial intelligence (AI) trained by machine learning (ML) algorithms as an amazing paradigm can be incorporated with blockchain to settle these issues. The data storing methods of blockchain can likewise be enhanced with the assistance of ML algorithms. In this paper, a two-tier authenticated consortium blockchain (TTA-CB) protocol is proposed for secure information partaking in Vehicle Edge Computing and Networks (VECONs). Utilizing a one-time password (OTP) based notoriety estimation calculation, the misbehaving vehicles are recognized. The use of Particle Swarm Optimization (PSO) understands the ideal data provider selection issue utilizing notoriety esteems. Exploratory outcomes demonstrate the importance of the proposed strategy, and the correlation results demonstrate that the proposed technique is unrivaled and secure.
Article
Consensus is one of the most important issues of a blockchain system because it is a necessary process to reach an agreement between a group of separated nodes that do not trust each other in a decentralized framework. Most existing blockchain consensus works assume that the time of block propagation among separated nodes during the consensus process is ignorable, i.e., a block always successfully reaches every participating node during a period of time that is far shorter than the mining time. However, when blockchain is used in vehicular ad hoc networks (VANETs), the block propagation time is no longer negligible since the dynamic connectivity of the moving nodes in a wireless environment brings opportunistic communication to blockchain consensus. In this article, we study the impact of mobility on block propagation under the single-chain structure in VANET. Specifically, we investigate the dynamics of block propagation from the macroscopic view and derive the closed-form expression of the single-block propagation time. Then, we characterize the blockchain forking as the multiblock competitive propagation. In this way, an approximate result on multiblock propagation time is discussed. An interesting finding is that higher mobility and more moving vehicles can speed up the block propagation. In addition, we also discover that distinct propagation capabilities of moving nodes contribute to the forking reduction in the blockchain consensus.
Article
Vehicular Ad-hoc Network enhances driving safety and enables various intelligent transportation applications by adopting the revolutionary vehicular wireless communication technology. This has attracted a lot of attentions from both academia and industry in recent years. Given the sophistication of vehicular manufacturing and the heterogeneity of intelligent transport terminals, performing vehicular authentication is of great importance. The existing schemes have largely considered vehicle security and authentication within a single administrative domain, which lacks supervision of the authority and entity in the intelligent transportation system. In this paper, we propose a multi-domain vehicular authentication architecture by introducing blockchain technique to build distributed trust and share cross-domain information among multiple administrative domains. To guarantee the anonymity and traceability, a pseudonym-based privacy-preserving authentication method is proposed. Specifically, considering the supervision of authority and the resilience to key escrow, we design a two-phase pseudonym distribution mechanism with the assistance of RSU proxy. We conduct in-depth security analysis by comparing with existing works, and deploy experiment to show the efficiency and feasibility of the proposed scheme in multi-domain scenario.
Article
The vehicular crowdsensing, which benefits from edge computing devices (ECDs) distributedly selecting autonomous vehicles (AVs) to complete the sensing tasks and collecting the sensing results, represents a practical and promising solution to facilitate the autonomous vehicular networks (AVNs). With frequent data transaction and rewards distribution in the crowdsensing process, how to design an integrated scheme which guarantees the privacy of AVs and enables the ECDs to earn rewards securely while minimizing the task execution cost (TEC) therefore becomes a challenge. To this end, in this paper, we develop a blockchain-based collaborative crowdsensing (BCC) scheme to support secure and efficient vehicular crowdsensing in AVNs. In the BCC, by considering the potential attacks in the crowdsensing process, we first develop a secure crowdsensing environment by designing a blockchain-based transaction architecture to deal with privacy and security issues. With the designed architecture, we then propose a coalition game with a transferable reward to motivate AVs to cooperatively execute the crowdsensing tasks by jointly considering the requirements of the tasks and the available sensing resources of AVs. After that, based on the merge and split rules, a coalition formation algorithm is designed to help each ECD select a group of AVs to form the optimal crowdsensing coalition (OCC) with the target of minimizing the TEC. Finally, we evaluate the TEC of the task and the rewards of the ECDs by comparing the proposed scheme with other schemes. The results show that our scheme can lead to a lower TEC for completing crowdsensing tasks and bring higher rewards to ECDs than the conventional schemes.
Article
While the vehicular network enables geographically distributed cooperative computation, its mature implementation has long been constrained due to lack of effective management platform. In this paper, employing the security and privacy attributes of blockchain, we propose a novel Blockchain-enabled Large-scale Parked Vehicular Computing (BLPVC) architecture to utilize the potential solar energy and vehicular computational resources in the outdoor parking lot. However, the uneven green power supply and random arrival time of electric vehicles compose the highly complex environment. Accordingly, in this paper, concerning on how to handle the efficient utilization of the distributed resources by blockchain technology, we propose an integrated optimization framework which leverages the green energy utilization and service latency limit among the processes of block generation, task computing, and communication, whereas such a design leads to the mixed-timescale stochastic optimization problem. To this end, corresponding to the dynamic solar energy arrival, we propose a shaped deep deterministic policy gradient (DDPG) algorithm to accelerate the learning rate of computational frequency control in the short-term stage; while in the long-term stage, for the mixed-integer programming (MIP) of task offloading and blockchain parameters adjustment, a series of transformation is employed to preserve convexity. Finally, experiments are carried out on Python demonstrating that the proposed scheme achieves a balanced performance between service latency and distributed resources, while the battery depreciation cost is heavily reduced.
Article
To meet the execution requirements of delay-sensitive services in vehicular edge computing (VEC) networks, vehicular services need to be offloaded to edge computing nodes. For complex, large-scale services, the services need to be migrated if the services are not completed before the vehicles leave the coverage of edge computing nodes. Trust and resource matching between areas thus become major problems. This paper studies the decision model of vehicular service offloading and migration. First, software-defined network (SDN) technology is introduced into the traditional network architecture, and a two-layer distributed SDN-controlled VEC network architecture is designed, which is divided into a domain control layer and an area control layer. In this framework, we use the consortium blockchain as a carrier to share network topology information between SDN controllers to prevent information leakage. We then established a service offloading and migration optimization problem model to minimize service execution delay, reduce energy consumption and maximize the throughput of the blockchain system. We describe the problem model as a Markov Decision Process (MDP), introduce a deep reinforcement learning (DRL) algorithm named asynchronous advantage actor-critic (A3C) and design a dynamic service offloading and migration algorithm (DSOMA) based on A3C to solve the problem. Simulation results show that DSOMA can increase the throughput of the blockchain system, and DSOMA is superior to the deep Q-learning (DQN) algorithm and greedy offloading algorithm in reducing service execution delay and system energy consumption.
Article
Wireless blockchain network is proposed to enable a decentralized and safe wireless networks for various blockchain applications. To achieve blockchain consensus in wireless network, one of the important steps is to broadcast new block using wireless channel. Under wireless network protocols, the block transmitting will be affected significantly. In this work, we focus on the consensus process in blockchain-based wireless local area network (B-WLAN) by investigating the impact of the media access control (MAC) protocol, CSMA/CA. With the randomness of the backoff counter in CSMA/CA, it is possible for latter blocks to catch up or outpace the earlier one, which complicates blockchain forking problem. In view of this, we propose mining strategies to pause mining for reducing the forking probability, and a discard strategy to remove the forking blocks that already exist in CSMA/CA backoff procedure. Based on the proposed strategies, we design Block Access Control (BAC) approaches to effectively schedule block mining and transmitting for improving the performance of B-WLAN. Then, Markov chain models are presented to conduct performance analysis in B-WLAN. The results show that BAC approaches can help the network to achieve a high transaction throughput while improving block utilization and saving computational power. Meanwhile, the trade-off between transaction throughput and block utilization is demonstrated, which can act as a guidance for practical deployment of blockchain.
Article
With the development of autonomous driving and the Internet of Vehicles, vehicle data communication and data security become more and more important. Blockchain which has transparency, decentralization and immutability nature is treated as a promising approach to support intelligent vehicle systems. However, due to the high data update overhead, vulnerable raw data storage policy and inflexible consensus algorithm, traditional blockchain technologies are not suitable in modern vehicular systems. Hence, we propose BUS, a blockchain data storage system that supports incremental data updating. Specifically, the system reduces the re-uploaded data size through smart contract and data partition to decrease the overhead. Besides, data replica and multi-data source addressing of index on the chain enhance the data reliability. In addition, an adaptive proof-of-work algorithm is developed, whose execution cost is dynamically adjusted based on nodes' behavior. It greatly improves the data record and updating efficiency. Comprehensive experimental results show that BUS can effectively improve the data updating efficiency with low overhead and fewer resources in intelligent vehicle scenarios.
Article
An unmanned aerial vehicle ad hoc network (UAANET) is an information sensing, analyzing, and transmitting network formed by multiple coordinated and collaborating UAVs. It is an emerging networking technology with a broad market prospect, but faces the problems of high dynamic topology and lack of trust. To address these issues, this article proposes a blockchain-em-powered trusted networking framework for UAANET, as well as the corresponding network architecture, protocol stack, key control signaling, and algorithms. To be more specific, blockchain is designed as a layer of distributed peer-to-peer security running on top of the physical UAANET. Three types of control signaling are designed, namely HELLO packet, topology control packet, and consensus packet. A max-min stable routing algorithm with three-dimensional link duration and a multipoint-relay-driven delegated Byzantine fault tolerance consensus mechanism are proposed for trusted networking of UAANET. The involved technical background and challenges are also detailed. These works together provide good references for scale deployment of UAANET in the near future.