Blockchain enabled Secure and Efﬁcient Reputation
Management for Vehicular Energy Network
Abid Jamal1, Muhammad Usman Gurmani1, Saba Awan1, Maimoona Bint E Sajid1, Sana Amjad1, Nadeem Javaid1,∗
1Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
Email: firstname.lastname@example.org, email@example.com,
firstname.lastname@example.org, email@example.com, firstname.lastname@example.org,
∗Corresponding Author: email@example.com; www.njavaid.com
Abstract—Blockchain (BC) based Vehicular Energy Network
(VEN) enables secure and distributed trading between the vehi-
cles. Furthermore, reputation management is a critical require-
ment for building trust in BC based VENs. However, the existing
BC based reputation schemes are vulnerable to replay attacks
due to insecure reputation veriﬁcation. Moreover, a BC based
VEN also requires a privacy preserving traceability mechanism
to prevent false information dissemination and fraudulent trans-
actions. Furthermore, a VEN also necessitates an efﬁcient storage
mechanism to reduce the storage overhead incurred by the BC
ledger. To address these issues, this paper presents a BC based
secure and efﬁcient reputation management scheme for VENs.
The proposed scheme provides a secure vehicles’ reputation
veriﬁcation mechanism to prevent the replay attacks. More-
over, the proposed scheme uses Elliptic Curve Digital Signature
Algorithm based pseudonym mechanism to enable conditional
anonymity and vehicles’ traceability. Furthermore, the proposed
scheme uses InterPlanetary File System to efﬁciently store the
vehicles’ reputation information and consequently, reduces the
storage overhead. Finally, performance and security analysis
is performed to show the effectiveness and practicality of the
The number of vehicles in the urban areas is increasing
at a rapid pace. This increase introduces multiple challenges,
including environmental pollution, road jams, trafﬁc accidents,
etc., –. To deal with these issues, Intelligent Transport
System (ITS) is introduced to effectively manage the trafﬁc
conditions in highly populated urban areas.
Vehicular Energy Network (VEN) is one of the prominent
applications of ITS, which has recently gained attention due to
its promising features like energy trading, information sharing,
load balancing, etc., –. Vehicles in a VEN use Dedicated
Short Range Communications (DSRC) protocol to commu-
nicate with the other vehicles to share information, trade
energy and broadcast announcement messages in the network.
However, as the conventional VENs rely on a centralized
server for the network management, it is vulnerable to the
Denial of Service (DOS) attacks and scalability issue. Hence,
several researchers have proposed decentralized solutions for
On the other hand, Blockchain (BC) is a distributed ledger
technology that was introduced by Satoshi Nakamoto in 2008
. With the popularity of Bitcoin, different variants of BC
have been introduced. Ethereum is one of the renowned BC
framework  that introduces the concept of smart contract
which enables the users to trade assets and share information
without the involvement of a third party.
Due to its prominent features, like transparency, data
integrity, availability, tamper-proof records, etc., the BC
technology can improve the conventional VENs –.
In BC based VEN, different set of vulnerabilities related to
privacy and security exist. Due to the open nature of BC, the
malicious vehicles can spread false information and perform
fraudulent transactions in the VEN. Moreover, the existing
BC based VENs lack effective vehicle traceability mechanism
to identify and revoke malicious vehicles. Furthermore, due
to the limited storage of VEN nodes, the current BC based
VENs are prone to data unavailability and they incur high
To overcome these issues, we propose a BC based secure
and efﬁcient reputation management scheme, which prevents
replay attack, enables conditional privacy and efﬁcient data
storage. The following is the list of our contributions.
•An effective vehicle reputation veriﬁcation mechanism is
proposed in which the vehicles’ ratings are stored in the
latest block to prevent the replay attacks.
•Elliptic Curve Digital Signature Algorithm (ECDSA)
based vehicle authentication mechanism is used to enable
conditional anonymity in VENs.
•InterPlanetary File System (IPFS) is used for ensuring
persistent data availability and efﬁcient data storage.
The rest of the paper is organized as follows. In section II, the
related work is presented. A problem statement, formulated
based upon the related work, is presented in section III. In
section IV, the proposed system model is shown. The working
of the proposed scheme is discussed in section V. The Security
analysis is presented in section VI, whereas the results are
shown in section VII. Finally, the conclusion is drawn in
II. RE LATE D WOR K
Recently, the researchers have focused on the applications
of ITS for reducing the environmental pollution caused by
the trafﬁc. The conventional centralized vehicular network
architecture fails to aid in these applications due to several
reasons, including scalability issue, increased security risks,
trust management, etc. To overcome these issues, decentralized
solutions are proposed.
In , the authors address the issue of security vul-
nerabilities in smart vehicles. They exploit a permissioned
BC based reputation scheme to prevent false information
dissemination in the network. However, their proposed rep-
utation scheme does not allow the less reputed vehicles to
regain their reputation values. In , authors propose One-
Time Password (OTP) and Artiﬁcial Intelligence (AI) based
reputation mechanism in vehicular edge computing to enable
secure data sharing. A secure BC based incentive scheme is
proposed in  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  address the issue of
malicious service provision in vehicular cloud network. They
propose a BC based trust management scheme by utilizing
three-valued subjective logic to identify the malicious service
providers. The authors in  address the issue of compu-
tationally intensive reputation and consensus mechanism in
vehicular energy network. They propose Proof of Work based
reputation scheme to reduce the mining cost. The authors in
 propose a BC based energy and data trading scheme.
Their proposed scheme uses smart contracts to handle trading
disputes and data redundancy.
The authors in  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 authors in  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  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 reuploaded
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 , authors address
the issue of high computational and storage cost in BC based
Internet of Vehicles. They propose a consortium BC enabled
edge computing system to reduce the communication cost and
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  propose
a BC enabled efﬁcient certiﬁcate revocation list management
scheme. Their proposed pseudonym shufﬂing mechanism re-
duces the storage cost of large number of pseudonyms. In
, 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 , the propose a
BC based distributed authentication scheme. However, their
proposed scheme is susceptible to single point of failure as
the users’ authentication information is stored in a central-
ized cloud server. In , the authors 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.
III. PROB LE M STATEM EN T
Reputation management is necessary for the vehicular net-
work to verify the trustworthiness of a vehicle before trading or
sharing information. The authors in  propose a reputation
scheme in which the vehicles prove their trustworthiness by
sharing the index of transaction, which contains their reputa-
tion value. However, this scheme is inherently vulnerable to
replay attacks as the malicious vehicles can share the index of
an old transaction to appear as reliable entities. Furthermore,
the authors in , use One-Time Address (OTA) mechanism
to prevent unique identiﬁcation of a vehicle. However, due to
the lack of conditional anonymity, the malicious vehicles can-
not be traced or removed from the network. Another common
issue in BC based vehicular networks is the high storage cost
due to the data redundancy and indeﬁnite growth of BC ledger.
To overcome this issue, the authors in  store the BC ledger
on pre-selected Roadside Units (RSUs) to save the storage
space. However, in addition to the increased communication
cost, their proposed solution is prone to scalability and data
IV. SYS TE M MOD EL
In this paper, we propose a secure and efﬁcient reputation
management scheme for VENs. The proposed model consists
of three phases, as shown in Figure 1. The ﬁrst phase is
registration phase in which the vehicles are registered with the
Certiﬁcate Authority (CA) by sending their identity informa-
tion. The second phase is vehicle trading phase. In this phase,
the secure trading is ensured by verifying the trustworthiness
of the vehicles on the BC. The third phase is the data storage
phase, wherein the RSUs store the users’ reputation data on
IPFS to save their storage. The proposed model depicted in
Figure 1, contains a mapping table of the limitations and their
solutions. The limitations ranging from L1 to L3 are mapped
with the solutions ranging from S1 to S3, respectively.
Req = Sigvi(P_keyvi,RIDvi,ts)
Input: (Sigvi , RIDVi)
Resp = SigCA(PIDvi)Authorized vehicle
joins the network
L1: Replay attacks due to
L2: Lack of traceability
mechanism for malicious
L3: Data unavailability due
to substandard storage
S1: Use of latest blocks for
S2: Conditional anonymity
to enable traceability
S3: Use of IPFS to ensure
TxReq = SigPRv1(req,ts,PIDv1)
TxRes = SigPRv2(res,ts,PIDv2)
TxReq = SigPRv1(req,ts,PIDv1)
TxRes = SigPRv2(res,ts,PIDv2)
TxReq = SigPRv1(req,ts,PIDv1)
TxRes = SigPRv2(res,ts,PIDv2)
- Verify Sigvi
- Generate PIDvi
- Store Enc(M(PID-> RID)) 3
Certificate AuthorityCertificate Authority
RoadSide UnitRoadSide Unit
Smart ContractSmart Contract
Fig. 1. Proposed System Model
The proposed system model contains the following entities.
1) Certiﬁcate Authority: The Certiﬁcate Authority (CA) is a
central trusted entity, which handles the registration process of
the vehicles and RSUs. In the proposed scheme, the CA stores
an encrypted copy of the mapping between the real ID and the
pseudo-ID of the vehicles to ensure vehicles’ traceability.
2) RoadSide Unit: RSUs perform multiple operations in
the vehicular networks. RSUs aid the vehicles in retrieving
reputation data from BC and the IPFS to ensure secure
transactions between the vehicles. The BC ledger is stored
on the RSUs, which contains all the information about the
reputation of the vehicles and the previous transactions. The
BC ledger stored on all RSUs ensures the data availability.
3) Vehicles: In the proposed system, the vehicles share
announcements with each other and the RSUs about the road
conditions. The vehicles also trade data and energy with each
other to increase their reputation value and earn monetary
4) Blockchain: In the proposed model, the BC is used to
store the reputation data of the vehicles in a distributed manner
to overcome the single point of failure issue. Moreover, it also
provides transparency, integrity and availability of the data.
5) Smart Contract: In the proposed model, vehicles use
smart contracts for requesting the reputation data of their trad-
ing partner from BC before initiating a trade. Moreover, RSUs
use smart contract for storing and updating the reputation data
of the vehicles in the BC.
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. The reputation data
of 100 vehicles is combined to form a single batch. The IPFS
returns a ﬁx sized SHA-256 hash for every batch. This hash
is then stored on the BC to ensure transparency.
V. PROPOSED SCHEME
In this section, the details of all phases of the proposed
scheme are presented. Some of the notations used in the
scheme are as following. V1and V2represent two vehicles
that perform trading. Whereas, RID and P ID are the real ID
and pseudo ID of the vehicles, respectively.
A. System Initialization
For system’s initialization, an Elliptic curve y2=x3+
ax +b mod p is selected. Here a,b∈Z∗
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 private key CAMS K and generating a master public
key CAM P K =CAM SK ×g. CA uses ECDSA for signing
the digital certiﬁcates. The signing key and verifying key of
CA are CAsig Key and C AverK ey , respectively.
B. Registration Phase
In this phase, the vehicle V1requests the CA for a
pseudo ID by sending its private information RIDV1=
(N ame, SSN , PlateN umber)over a secure channel. The
CA ﬁrst veriﬁes the RIDV1by checking the list of existing
users and the blacklist to see if the vehicle is malicious. After
veriﬁcation, the CA generates a pseudo ID P IDV1for the
vehicle V1. The CA also generates a mapping between RIDV1
and P I DV1and stores it in the encrypted form as which is
described as. Mapping(P I DV1)=EncC AMP K (P I DV1−>
RIDV1). This mapping ensures the vehicles’ traceability
while preserving their privacy.
C. Vehicle Trading Phase
After registration, the vehicles become a part of the
network and can trade with other members of the network.
In the trading process, the vehicle V1ﬁrst sends a trading
request signed with its private key to V2for trading the
data, V11−> V2:T xReq =(req, ts, P I DV1, SigV1sigK ey ).
Here req is the requested data, ts is the timestamp, P I D is
pseudo ID and Sig(.)shows that the request is signed. When
the vehicle V2receives the request, it extracts the PI DV1
from the T xReq and sends it to the RSU for checking the
V2−> RSU :RepCheckReq =(P IDV1, ts, S igV2sigKey )
RSU −> V2:repV alue(V1)
The RSU returns the reputation value by requesting the data
from the BC via smart contract. After receiving the reputation
information of V1, the V2initiates the trade with V1if the
reputation value of V1is above the pre-deﬁned threshold.
D. Data Storage Phase
In this phase, the RSU stores the reputation data of the
vehicles on the IPFS to reduce the storage cost of BC. The
reputation data is divided into the batches of 100 users before
it is uploaded to the IPFS. Each batch is encrypted with the
RSU’s public key RSUpk before it is stored on the IPFS
to prevent malicious data access. The request IP F SReq =
EncRS Upk (ReputationData||ts)is sent to IPFS. In return,
the IPFS sends a ﬁxed length SHA-256 hash to the RSU which
is then stored on the BC ledger.
VI. SECURITY ANA LYSIS
In this section, we discuss two of the existing BC based
VEN vulnerabilities and their countermeasures.
Fig. 2. Time cost of OTA and ECC
A. Replay Attacks Prevention
When a valid data transmission is maliciously repeated,
it is termed as a replay attack. As discussed in section III,
the vehicles in the BC based vehicular networks prove their
trustworthiness by sharing the index of the transaction, which
contains their reputation value. This approach is vulnerable to
the replay attacks as the vehicles can share older transaction
indexes to appear as more trustworthy. To overcome this issue,
our proposed scheme stores all of the reputation information in
the latest block using IPFS. The users are restricted to only use
the latest block for verifying the trustworthiness of a vehicle.
B. Conditional Privacy Preservation
In the proposed scheme, the pseudonym certiﬁcates are used
for hiding the real identity of the vehicles. The real identity
information of the vehicles is stored with the CA so that in case
of disputes or misbehaviour, the true identity of the malicious
vehicles can be exposed. In , authors use OTA method to
prevent privacy leakage due to data linkage. However, their
proposed OTA scheme lacks traceability feature, due to the
which the malicious vehicles cannot be identiﬁed or removed
from the network.
VII. RES ULTS A ND DISCUSSION
The proposed scheme is compared with existing solutions
provided in the literature. For the transactions signing, we have
compared the use of OTA scheme with ECDSA. Moreover, we
have compared the use of BC and IPFS for data storage. Also,
we have related response delays of vehicles with the malicious
Figure 2 shows the comparison of different cryptographic
operations OTA scheme, used in , with the ECDSA based
pseudonym certiﬁcate generation scheme. It can be observed
that the OTA takes signiﬁcantly longer time to generate keys
due to the use of Kerl hashing algorithms. In OTA scheme,
each address is used only once to prevent the private key leak-
age. However, due to immense computational cost, it cannot
fulﬁl the requirement of quick authentication of fast-moving
vehicles in the vehicular networks. Hence, we utilize ECDSA
which enables quick authentication and privacy preservation.
The results show the comparison of both schemes in terms
Fig. 3. Storage cost comparison of BC and IPFS
Fig. 4. Malicious vehicle detection using delays in response time
of computational time required for key generation, signature
generation and veriﬁcation.
Figure 3 shows the comparison of storage cost of storing
reputation data directly on BC and its IPFS hash. It is evident
from the ﬁgure 3 that storing the actual data on BC is
a resource intensive task as the same copy of the data is
needed to be stored on every node. Authors in  have
stored the BC ledger on selective RSUs to overcome the
overwhelming storage cost; however it introduces the issues
of data unavailability and increased communication cost due
to increased number of data retrieval requests. Hence, to
overcome this issue, we use IPFS to store the actual data and
store only the IPFS hash on the BC. As the IPFS returns a
ﬁxed size SHA-256 hash value for the data irrespective of its
size, hence, it is an efﬁcient approach to store the IPFS hash
of the data on BC instead of storing the actual data.
Figure 4 shows the time delays in the vehicle’s request and
response. In a vehicular network, the vehicle sends requests
to other vehicles for information sharing or energy trading.
The other vehicle has to respond with the correct information
and prove its trustworthiness. The results depict that when a
vehicle share authentic reputation information with its peer, the
response time generally follows a same trend. However, when
a vehicle shares fake reputation information, it takes a longer
than the authentic response like the 7th request in ﬁgure 4. The
reason of taking longer time is that, the malicious vehicle will
need to generate fake reputation information before sending
the response. Hence, we have used the delay in response time
to identify the malicious vehicles.
In this paper, we propose a BC based secure and efﬁcient
reputation management scheme to prevent replay attacks,
enable conditional anonymity and reduce the storage cost of
VEN. We have used IPFS to efﬁciently store the reputation
data of the vehicles in the latest block to enable secure
reputation veriﬁcation. Moreover, ECDSA is used for enabling
conditional anonymity. The security analysis is performed
to show the robustness of the proposed scheme. Also the
performance analysis shows the practicality of the proposed
scheme. In future, this scheme will be further extended to
include distributed revocation mechanism.
 Y. Li and B. Hu, ”An Iterative Two-Layer Optimization Charging and
Discharging Trading Scheme for Electric Vehicle Using Consortium
Blockchain,” in IEEE Transactions on Smart Grid, vol. 11, no. 3, pp.
2627-2637, May 2020, doi: 10.1109/TSG.2019.2958971
 Q. Feng, D. He, S. Zeadally and K. Liang, ”BPAS: Blockchain-
Assisted Privacy-Preserving Authentication System for Vehicular Ad
Hoc Networks,” in IEEE Transactions on Industrial Informatics, vol.
16, no. 6, pp. 4146-4155, June 2020, doi: 10.1109/TII.2019.2948053
 Li, Kang, Wang Fat Lau, Man Ho Au, Ivan Wang-Hei Ho, and Yilei
Wang. ”Efﬁcient message authentication with revocation transparency
using blockchain for vehicular networks.” Computers & Electrical En-
gineering 86 (2020): 106721.
 Posner, Jason, Lewis Tseng, Moayad Aloqaily, and Yaser Jararweh.
”Federated Learning in Vehicular Networks: Opportunities and Solu-
tions.” IEEE Network 35, no. 2 (2021): 152-159.
 Kudva, Sowmya, Shahriar Badsha, Shamik Sengupta, Ibrahim Khalil,
and Albert Zomaya. ”Towards secure and practical consensus for
blockchain based VANET.” Information Sciences 545 (2021): 170-187.
 Wang, Eric Ke, Zuodong Liang, Chien-Ming Chen, Saru Kumari, and
Muhammad Khurram Khan. ”PoRX: A reputation incentive scheme for
blockchain consensus of IIoT.” Future Generation Computer Systems
102 (2020): 140-151.
 Nakamoto, Satoshi. Bitcoin: A peer-to-peer electronic cash system.
 Buterin, Vitalik. ”A next-generation smart contract and decentralized
application platform.” white paper 3, no. 37 (2014).
 Firdaus, Muhammad, and Kyung-Hyune Rhee. ”On Blockchain-
Enhanced Secure Data Storage and Sharing in Vehicular Edge Com-
puting Networks.” Applied Sciences 11, no. 1 (2021): 414.
 Javaid, Uzair, Muhammad Naveed Aman, and Biplab Sikdar. ”A scalable
protocol for driving trust management in internet of vehicles with
blockchain.” IEEE Internet of Things Journal 7, no. 12 (2020): 11815-
 Ma, Zhuo, Junwei Zhang, Yongzhen Guo, Yang Liu, Ximeng Liu, and
Wei He. ”An efﬁcient decentralized key management mechanism for
VANET with blockchain.” IEEE Transactions on Vehicular Technology
69, no. 6 (2020): 5836-5849.
 Ren, Yanli, Xiangyu Li, Shi-Feng Sun, Xingliang Yuan, and Xinpeng
Zhang. ”Privacy-preserving batch veriﬁcation signature scheme based
on blockchain for Vehicular Ad-Hoc Networks.” Journal of Information
Security and Applications 58 (2021): 102698.
 Zhang, Qikun, Yongjiao Li, Ruifang Wang, Jianyong Li, Yong Gan,
Yanhua Zhang, and Xiao Yu. ”Blockchain-based asymmetric group key
agreement protocol for internet of vehicles.” Computers & Electrical
Engineering 86 (2020): 106713.
 Oham, Chuka, Regio A. Michelin, Raja Jurdak, Salil S. Kanhere, and
Sanjay Jha. ”B-FERL: Blockchain based framework for securing smart
vehicles.” Information Processing & Management 58, no. 1 (2021):
 Gawas, Mahadev, Hemprasad Patil, and Sweta S. Govekar. ”An integra-
tive approach for secure data sharing in vehicular edge computing using
Blockchain.” Peer-to-Peer Networking and Applications (2021): 1-19.
 Khalid, Adia, Muhammad Sohaib Iftikhar, Ahmad Almogren, Rabiya
Khalid, Muhammad Khalil Afzal, and Nadeem Javaid. ”A blockchain
based incentive provisioning scheme for trafﬁc event validation and in-
formation storage in VANETs.” Information Processing & Management
58, no. 2 (2021): 102464.
 Xu, Shilin, Caili Guo, Rose Qingyang Hu, and Yi Qian. ”BlockChain
Inspired Secure Computation Ofﬂoading in a Vehicular Cloud Network.”
IEEE Internet of Things Journal (2021).
 Yahaya, Adamu Sani, Nadeem Javaid, Muhammad Umar Javed,
Muhammad Shaﬁq, Wazir Zada Khan, and Mohammed Y. Aalsalem.
”Blockchain-Based Energy Trading and Load Balancing Using Contract
Theory and Reputation in a Smart Community.” IEEE Access 8 (2020):
 Sadiq, Ayesha, Muhammad Umar Javed, Rabiya Khalid, Ahmad Al-
mogren, Muhammad Shaﬁq, and Nadeem Javaid. ”Blockchain based
Data and Energy Trading in Internet of Electric Vehicles.” IEEE Access
 Akhter, A. F. M., Mohiuddin Ahmed, A. F. M. Shah, Adnan Anwar, A.
S. M. Kayes, and Ahmet Zengin. ”A blockchain based authentication
protocol for cooperative vehicular ad hoc network.” Sensors 21, no. 4
 Arora, Sandeep Kumar, Gulshan Kumar, and Tai-hoon Kim. ”Blockchain
Based Trust Model Using Tendermint in Vehicular Adhoc Networks.”
Applied Sciences 11, no. 5 (2021): 1998.
 Yin, Yuyu, Youhuizi Li, Bingyue Ye, Tingting Liang, and Yu Li. ”A
Blockchain-based Incremental Update Supported Data Storage System
for Intelligent Vehicles.” IEEE Transactions on Vehicular Technology
 Mei, Qian, Hu Xiong, Yanan Zhao, and Kuo-Hui Yeh. ”Toward
Blockchain-Enabled IoV with Edge Computing: Efﬁcient and Privacy-
Preserving Vehicular Communication and Dynamic Updating.” In 2021
IEEE Conference on Dependable and Secure Computing (DSC), pp. 1-8.
 Lei, Ao, Yue Cao, Shihan Bao, Dasen Li, Philip Asuquo, Haitham
Cruickshank, and Zhili Sun. ”A blockchain based certiﬁcate revoca-
tion scheme for vehicular communication systems.” Future Generation
Computer Systems 110 (2020): 892-903.
 Shrestha, Rakesh, Rojeena Bajracharya, Anish P. Shrestha, and Seung
Yeob Nam. ”A new type of blockchain for secure message exchange in
VANET.” Digital communications and networks 6, no. 2 (2020): 177-
 Zheng, Dong, Chunming Jing, Rui Guo, Shiyao Gao, and Liang Wang.
”A traceable blockchain based access authentication system with privacy
preservation in VANETs.” IEEE Access 7 (2019): 117716-117726.
 Benarous, Leila, Benamar Kadri, and Ahmed Bouridane. ”Blockchain-
Based Privacy-Aware Pseudonym Management Framework for Vehicular
Networks.” Arabian Journal for Science and Engineering (2020): 1-17.
 Luo, Bin, Xinghua Li, Jian Weng, Jingjing Guo, and Jianfeng Ma.
”Blockchain enabled trust-based location privacy protection scheme in
VANET.” IEEE Transactions on Vehicular Technology 69, no. 2 (2019):
 Pu, Yuwen, Tao Xiang, Chunqiang Hu, Arwa Alrawais, and Hongyang
Yan. ”An efﬁcient blockchain based privacy preserving scheme for
vehicular social networks.” Information Sciences 540 (2020): 308-324.