=Paper=
{{Paper
|id=Vol-3010/PAPER_11
|storemode=property
|title=Secure and authenticated protocols for VANETS
|pdfUrl=https://ceur-ws.org/Vol-3010/PAPER_11.pdf
|volume=Vol-3010
|authors=Heena Khanna,Manmohan Sharma,Dhavleesh Rattan
}}
==Secure and authenticated protocols for VANETS==
https://ceur-ws.org/Vol-3010/PAPER_11.pdf
Secure and Authenticated Protocols for VANETs
Heena Khanna a,b, Manmohan Sharma b Dhavleesh Rattan c
a
PCTE Group of Institutes, Ludhiana, Punjab, India
b
Lovely Professional University, Phagwara, Punjab, India
c
Punjabi University, Department of Computer Engineering, Patiala, India
Abstract
With the ever-growing increase in the number of vehicles on road today, the security of the
driver and the passengers has become more crucial and challenging than ever before in
history. A secure and authenticated message transmission amongst the vehicles is the desired
solution everyone is aiming at. The advancements in digital communication have given a new
horizon to Vehicle-Vehicle communication. Nevertheless, authentication and privacy is still
an open issue to be addressed in order to have a robust VANET. This survey compiles the
contribution by the researchers for a Secure and Authenticate formulation of VANET.
Towards the end, we enlist some open issues which can make a base for future research
work.
Keywords 1
V2V communication, Vehicular Communication, Wireless Communication, V2V Network,
VANET, Vehicular Network
1. Introduction
Two or more vehicles communicating with each other during their drive on road is stated to be
V2V communication [1]. To avoid any probable crash, vehicles connected with each other shares the
details about location, directions, swift turns, speed, brakes & also for emergency. Mesh network is
used by connected vehicles to send, receive and retransmit signals further to communicate. Range for
sending signals is upto 300 meters & signals are sent in omni-diretion creating 30 degrees awareness
in the vincity (US Department of Transportation). Dedicated Short Range Communication (DSRC) is
used to establish the communication. DSRC is a dedicated wireless communication channel used for
automotive usage to establish one way or more short range connections. Federal Communication
Commission (FCC) and International Organization Standard (ISO) have approved DSRC. Ad- hoc
network thus created as nodes with Vehicle is called as Vehicular Ad-Hoc Network (VANET) which
further is a subset of Mobile Ad-Hoc Network (MANET ) [2]. This VANET comprises of the moving
vehicle as well as stationary infrastructure called as Road Side Units(RSU) [3]. Vehicle
communication to any other physical device is another variation in this and termed as Vehicle to
Infrastructure. It is also termed as Internet of Vehicles in continuation and parallel to Internet of
Things (IoT) [4].
VANET seems to be a promising solution to have secure transportation but it comes with a lot of
challenges. There can be multiple types of attacks on various layers of networks which can be
categorised in either Active or Passive ones. Most of the attacks are found at Network Layer which is
the most crucial to keep the network secure[3], in this survey the authors discusses all the possible
attacks in VANET. To say it in a crux form, VANET needs to be secured for privacy, authenticity
and shall ensure secure message dissemination [5]against all the mentioned attacks [3].
Algorithms, Computing and Mathematics Conference, August 19 – 20, 2021, Chennai, India.
EMAIL: heena.pkalra@gmail.com (Heena Khanna)
ORCID: 0000-0003-0785-8459 (Heena Khanna)
© 2021 Copyright for this paper by its authors.
Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).
CEUR Workshop Proceedings (CEUR-WS.org)
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There are many researchers who have come up with some potential protocols to provide a secure
and authenticate VANET which are discussed and compared at length in this survey. The protocols
have been clumped according to their core technique and have been elaborated according to their year
of proposal. The main focus of this survey is to compile the significant contributions in VANET in the
last decade despite of the technology so that it can facilitate the group of researchers who are working
in the same direction.
This work is categorized in three major segments. In the first segment, the related surveys have
been articulated for their contribution. In the second segment, we categorise the protocols according
to their techniques and compare their progress and results. In the last segment we lay down the
learning from all the existing protocols and list the potential concerns for future researches.
2. Related Surveys
The research progress in V2V communication has been reviewed by many authors. This section
summaries some of the significant researches being done in the last decade.
[5] discusses comprehensively about various privacy preserving and authentication techniques
used in Vehicular Ad-Hoc Network. The survey compared the work done in the field of security &
authentication based on ID-Based, RSU based Key Authentication, Cryptography based bilinear
pairing and smart card based protocols. It also shed light upon the protocols that addressed the
overhead in the PKI based methods. Not only that, the work also compared the protocols that use
message aggregation & cooperative message authentication including batch verification. The survey
concluded that three major areas need the robust solutions namely a) authentication of the messaged
as well as the vehicles. b) Secure message dissemination and c) user privacy. [6] unfolds how the
progress made in the V2V communication has not only given a modern approach to the
Transportation but has given hackers the access to the life of the people travelling in the vehicle.
Manifesting the point authors have looked upon all major attacks that have been made in the recent
past in sensing, communication and control layers. The authors also presented an extensive study on
all prospective attacks in V2X communications giving a contrast of their detection probability,
properties and ease of attack. Towards the end paper unfolds various Machine Learning & Blockchain
based solutions to deal the aforementioned attacks. [3] categorized the attacks on V2V
communication on the basis of the Network Layer, being Active or Passive attack and type of attack.
Along with the listing and elaborating the attacks authors talked about the proposed solutions which
are given by the researchers for each of the attacks. Moreover, it is concluded that a protocol is
required which can deal with all types of attacks and provide a mechanism where a trust system is
build amongst the people in the Vehicular Network. [7] grouped the attacks in five security services
namely Availability, Confidentiality, Authenticity, Integrity and Non-Repudiation and listed the
attacks under them and analyzed the authentication schemes for each one of them. Authors also
studied various Network & Mobility Simulators. [8] presented the discussion on various algorithms
using Machine Learning as a major contributor in safe and authenticated message transmission in
V2V. Authors also discussed that there is a need of an algorithm which not only protect from DoS
attacks but covers the damage from other attacks as well.
[9] present survey on the researches being done for wireless communication in Vehicles related to
their applications in real life, their corresponding protocols and multiple security issues. Authors have
analyzed all the researches for their strengths and weaknesses for future work perspectives. [10] gave
a contrast of various security issues over the VANET and listed the proposed solutions to handle those
issues. The analysis also mentions some motivation for the future work in the same direction. [11]
focused how urbanization is leading to increase traffic in the cities and consequently the need of
secure data transmission is highlighted. Moreover the authors logged a range of researches talking
about inter transmission o f the packets in multiple models of communication. Routing scalability and
reliability can be assured using clustering says [12]. The authors made a taxonomy of the clustering
techniques used for selection of cluster head, affiliation and overall management. Not only the
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benefits but the shortcomings of the algorithms have also been analyzed. The requirements of modern
cars and the security issues and proposed solutions are listed by [13]. Whereas, the importance of
Encryption and authentication is highlighted by [14] in their survey where the a comparative study is
presented for the existing algorithm for VANET. Working on VANET requires the know-how of
various Simulation tools which is studied and analyzed by [15] in their paper. They also gave contrast
between various attacks and mechanisms used to deal with them. [16] Emphasizes on the
authentication for VANET and therefore did a survey on various schemes available for ensuring the
authentication. [17]not only emphasized upon the existing security threats but explores on the possible
attacks in future which provides a motivation to the researchers to explore and work on their possible
solutions. Countermeasures for priori and prosteriori are discussed and analyzed by [18] and a sketch
had been proposed for the same alongside the limitations and tensions in VANET then were
elaborated and compared.
Table 1: A summary of all the reviews and surveys
Year Paper Survey
2020 [5] Secure authentication and privacy-preserving techniques in Vehicular Ad-hoc
Networks (VANETs)
2020 [6] Cyber security challenges in vehicular communications
2020 [3] A Survey on Security in VANETs
2019 [7] A Survey on Recent Advances in Vehicular Network Security, Trust, and Privacy
2018 [8] Intelligent and Secure Vehicular Network using Machine Learning
2018 [9] Vehicular ad-hoc network (VANET): Review
2018 [10] A systematic review on security issues in vehicular ad hoc network
2017 [12] A Comparative Survey of VANET Clustering Techniques
2017 [13] Security and privacy in vehicular communications: Challenges and opportunities
2017 [14] A review on VANET security attacks and their countermeasure
2016 [15] Recent Advances in VANET Security: A Survey
2016 [16] A survey on authentication schemes of VANETs
2012 [17] Survey on security attacks in Vehicular Ad hoc Networks (VANETs)
2009 [18] Safety and Privacy in Vehicular Communications
3. Analysis of Existing Work
This section elaborates various researches being done over a decade for secure Vehicle to Vehicle
communication. We have categorized the algorithms in specific categories whereas some of the algorithms are
common and fall in more than one category.
3.1. Various clustering based algorithm for routing techniques in VANET
There are five different categorisation of VANET routing algorithm on the basis of the area and/or
application. They are, Geo cast routing protocol, Cluster based routing protocol, Broadcast routing protocol,
Topology based routing protocol and Position based routing protocol. [19] Over the years the researches have
proposed various models choosing a specific or a hybrid approach to have an efficient and secure model of
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VANET. Out of all these categories, clustering based algorithms have been explored the most and given some
significant contribution in VANET. In this section, various clustering routing algorithms have been compared
and analyzed.
[20] proposed a location based routing protocol with cluster based flooding for VANET. The performance of
this algorithm has considered a positional routing protocol called LORA_CBF and also with two non-positional
routing algorithms AODV[21] and DSR [22] . The results showed that the performance of positional based is
better than the non-positional ones. [23] came up with a clustering based algorithm with delay tolerance. It
worked on route discovery for data dissemination following the clustering techniques. It performed better in
terms of cost, overheads , stability of the clusters, packet loss ration and end-to-end delay when compared with
[24]&[25].
In [23] clusters are formed on the basis of the average speed of the vehicles whereas [26] grouped the
vehicles with long travel time and less deviation in speed is selected as Cluster Head and/or Improved cluster
head. Due to the same [26] proved showed lower end-to-end delay as compared to CBLR[27].
[28]shared an improved Genetic algorithm-based route optimization technique (IGAROT) which used K-
Means Clustering to remove road anomalies. When the algorithm was compared to GA, IGAROT showed
42.0% , 75.7% and 4.24% better results in high, medium and low car density environment respectively.
Table 2: Various clustering based algorithm for routing techniques in VANET
Year Paper Technique/Method Focus Strength & Result
Published Weakness
2004 [20] Location Routing Route It is ideal for Analyzed with the non-positional
Algorithm with Discovery, the algorithms AODV[21] & DSR [22] with
Cluster-Based Time, End dynamically the positional based LORA-CBF and it
Flooding (LORA- to End changing proved to be a better
CBF) Delay, topologies,
PDR large
networks &
high
mobility.
2017 [23] Cluster-based On- End to It costs less Performed better than LID[24] & HD[25]
demand End than [24] & in terms of cluster stability
Delay tolerant Delay, [25] due to
routing (CODE) Packet the
Loss minimum
Ratio, overhead
Routing
Overhead,
Head
Change
Ratio,
Member
Change
Ratio
2019 [28] Improved Genetic Received Prompt The proposed methodology performs
algorithm-based signal notifications better that the conventional genetic
route optimization Strength, of the algorithm in various car density scenarios
technique transmit agencies
(IGAROT) power, involved in
frequency road
and path maintenance.
loss
2016 [26] Vehicle with long End-End Scalable, Has lower end-to-end delay as compared
travel time and less Delay Efficient and to CBLR
deviation in speed distributed
is selected as
Cluster Head//
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Improved cluster
head
3.2. Fog Computing Based Algorithms for Security
[29]Discussed about various perspectives of data transmission in Vehicles. The paper analyzed various
available models for data transmission like 3G and 4G cellular networks, RSUs, Mobile Cloud Computing etc
and also analyzed their shortcomings in terms of expense and availability. They proposed to utilize the idle
parked and moving vehicles as both computational and communication vehicles. The huge potential of VFC is
taken forward to make V2V communication better. [30]Has worked upon reducing the hand off time and
increasing the throughput for the vehicular data transmission in Fog computing. The research proposes a
solution called as CVFH – A cross Layered and Neighbouring vehicle aided fast handoff wherein they focussed
upon two major strategies to achieve their target of reducing the hand off and increasing the throughput during
the high speed of Vehicles and High rate of packet transfer. CVFH suggests that in order to decrease hand off
delay the Vehicle can choose the Access Point used by the neighbouring Vehicle. Secondly CVFH suggests that
the Vehicle shall carry on with the existing Access Point by the time a new connection is established. The
simulations have shown CVFH to be a better performer as compared to IEEE 802.11 [31]Proposed a data
dissemination model to address the issues involved in Fog Computing while transferring High Volume and non
urgency based data transmission. The research also focuses on the fact that the fog model becomes expensive
and how to utilize the fog Based Computing efficiently. Therefore they proposed Delay Tolerable
Network(DTN) approach . In this approach they assign different role to Cloud and Fog Severs. Here, the Cloud
is given the job to manage data flows & content queries where as the Fog Servers are dedicated to disseminate
data using Delay Tolerant Network. The research results showed that their model depicts a higher delivery
success ratio and less delay to ensure a better system to disseminate important data in Fog Computing.
[32]Initiated to work on a model that creates a layer in between the Vehicle and the server to speed up the data
transfer. Just like when the client send a request to the server and cache memory maintains the information for
better processing the next time. They have proposed a model called SIVNFC which prevents DoS Attacks
across the network. [33]
Have done an analysis to check the data transmission on 28GHz. In order to overcome the problems to high
level of interference and High Packet Error they have done a deep interference analysis to derive the right
expressions of Packet Error Probability and Ergodic Capacity. The same has been simulated extensively to be
proven to next revolutionary step in V2V Communication.
[34] Introduced an intermediary fog layer to improve latency in Vehicle to Vehicle communication. The
algorithm works on the efficiency in terms of improving the delay in the messages. To ensure the authentication
it used Long Term & Short Term Pseudonym/Keys. [35]integrated hybrid optimization techniques for
authentication of the network. It integrated Cuckoo Search Algorithm, Firefly Neural Network, Firefly
Algorithm and Key Distribution Establishment in the protocol to ensure the network is prevented from DoS and
SNI Attacks. The results showed improved throughput and less jitter. [36]extended the research and introduced
the implementation of Artificial Bee Colony (ABC) and Genetic Algorithms to detect real time DoS attacks in
IEEE 802.11p. Algorithm is also capable to classify between genuine and attacked vehicles with the help of
Feed forward back propagation neural network (FFBPNN). The algorithm proved to give 92% accuracy and
reduced the jitter by 72%.
To ensure the safe communication in VANET, trusted authority (TA) comes into the picture. Self
authentication amongst the RSU and Vehicles can diminish the burden of TA. [37] proposed a fog based model
for anonymous authentication to ensure real time communication and reduced pressure on TA using pseudonym
based tracking mechanism to update and track. The algorithm gave promising results in terms of privacy
protection & authentication. Where[37] talked about anonymous authentication [38] proposed an algorithm for
mutual authentication and generates a secret key for secure communication between two vehicles. It ensures
privacy protection and claims practicality for the implementation reducing the communication cost.
Table 2 lists all the Fog Based protocols with their comparison.
Table 3: Fog Computing Based Algorithms for Security
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Year Paper Technique/Method Focus Strength & Result
Published Weakness
2017 [34] The authors Security Latency of Lesser Delay
introduce the key transfer
concept of Fog is reduced
Computing and due to the
used to the concept Fog Node.
of LTP/LTK &
STP/STK
2019 [35] A Fog integrated Security Prevents the Throughput 8100 at PIR 0.02
VANET Scheme network PIR 0.001 to 0.02. Maximum jitter is
compared with from DoS 96ms
Firefly and Cuckoo and SNI
2019 [36] VFC with Hybrid Security Provides real 92% Prediction accuracy . Reduced the
Optimization time jitter by 72%.
Algorithm like detection of
Cuckoo, Firefly & HDSA in
ABC IEEE802.11p
2017 [37] Fog Computing & d Anonymous Ensured privacy protection and
pseudonym-based Authentication efficient authentication.
batch anonymous
authentication
2019 [38] Authenticate Key Security Improved Communication &
Agreement without Computation Cost
bilinear pairing
3.3. ID & Signature Based Algorithms for Batch Authentication
The need of VANET came into the picture when the number of vehicles increased due to urbanization and
affordability of vehicles. Initially horns, hand waves and other mediums of traffic controls were sufficient and
gradually the traffic police came into the picture. Now, with the advancement of technology & digitization the
call for VANET has tremendously increased so as to improvise the transportation system and ensure smooth and
safe travel. However, technology always comes with a threat of security & authentication. In order to
authenticate the sender of the information various protocols have been introduced. The protocols can be
categorized into two heads, individual authentication & batch verification. With the increased number of
vehicles, one-to-one authentication becomes impossible & inefficient and therefore the concept of Batch
Scheme of authentication proved itself to be more effective [39]. [39] have integrated Bilinear pairing to
authenticate the signatures in batch and performance proved the algorithm to be performing better than [40] and
is also capable to handle replay and non-repudiation. However, it still lacks when it comes to identifying illegal
signatures. To overcome the shortcomings of [39], [41] came up with another algorithm after analyzing the
work of [41] and arriving at a conclusion that it lacks the capability to handle impersonation attack. The
algorithm is based upon the four step process Key Generation & pre-distribution, pseudo identity generation,
message signing and message verification. Bilinear pairing has been recognized as one of the most complex
operation when we talk of cryptography in modern times [42]. To provide a better an simpler mechanism a set
of researchers have come up with CPAA based schemes without integrating Bilinear pairing. [42] Proposed a
scheme which supports privacy protection and mutual authentication at the same time. The proposed scheme
could be used for V2I and V2V both. Whereas [43] continued the work on CPAA and integrated One way Hash
function and Elliptic Curve Cryptography provide a scheme with lesser cost of computation and
communication. To reduce the cost even more [44] suggested to opt for aggregate signature instead of individual
signature verification. They integrated Elliptic Curve Cryptosystem. The research results show that the signature
verification time has improved from 94.3% to 92.7%.
Table 4: ID & Signature Based Algorithms for Batch Authentication
Year Paper Technique/Method Focus Strength & Result
Published Weakness
2013 [39] Batch Scheme Authentication Secure & Compared with [40] and performed
based on Bilinear Efficient. better in terms of efficiency
124
pairing Can handle
replay
attack and
non-
repudiation
2014 [41] Batch Scheme Authentication Works on impersonation attack and
improved version of [39]
2015 [42] Conditional Authentication Could be Improved communication &
Privacy-Preserving used for computation cost
Authentication V2I and
(CPPA) without V2V both.
bilinear pairing Easier to
deploy
2016 [45] DiffieHellman is Security Vehicles Improved confidentiality,
used to ensure with thin authentication, access and
security & Discrete network are availability. PDR 98%.
Logarithmic benefitted End-to-end delay is 0.16
encryption scheme as it works
is used for on secure
Cryptography. positioning
algorithm.
2019 [43] ID Based Signature Authentication Lower computational cost due to
Scheme without batch signature verification
bilinear paring
IBS-CPAA added
to Elliptic Curve
Cryptography &
general one way
Hash Function
2018 [44] Certificate less Authentication Useful for Improved communication &
aggregate signature V2I, computation cost. Reduced
without pairings reduced computing time. Verification time is
cost of 450ms for 1000signatures, improved
verification. by 94.3% to 92.7%
3.4. Smart Card Based Algorithms for Authentication & Security
In the last decade Smart Card Based authentication has been explored more than ever before. They have an
incredible capacity to hoard enormous amount of data with the help o f embedded circuit chip and memory chip.
Smart cards offer a strong security base and have been used in many authentication algorithms, encryption
techniques and asymmetric key services. [46]
Researchers have explored Smart Cards authentication capabilities for VANET as well. [47]’s PAAVE
generates on-the-fly anonymous keys amongst RSU and the vehicles. Their results show improved efficiency,
Communication Overhead and Computational time. [48] continued the work to provide an even more efficient
way which not only diminishes the cost but also withstands attacks like offline password guessing attack, smart
card loss attack, impersonation attack and some more. [49] proposed Anonymous & light weight scheme for the
authentication of User and the message at not only authentication stage but also at password change and data
transmission phases as well. The protocol can deal with offline password guessing attack and impersonation
attack and also works on Packet loss ratio & latency. All these protocols used Smart Card for anonymous
authentication whereas [50] came up with an authentication protocol which uses real identity of the drivers. It
uses Spanish eICard and ensured 60-70% correctly obtained identities.
Table 5: Smart Card Based Algorithms for Authentication & Security
Year Paper Technique/Method Focus Strength & Result
125
Published Weakness
2010 [47] PAAVE- Authentication Generates the Improved efficiency,
Anonymous &Security anonymous Communication Overhead and
authentication using keys on the Computational time.
Smart Cards fly for vehicle
s and RSUs.
Vehicle has to
store one
cryptographic
key
2014 [48] Efficient Authentication Can resist Improved Computational &
Authentication & Security offline Communication Cost.
Protocol password
Ensures anonymity guessing
by dynamically attack, smart
generated login ids card loss
attack,
impersonation
attack, DOS
Attack.
Provide
anonymity
preservation
2017 [49] Anonymous & light Authentication Can deal with More than 50% of Computational
weight scheme for & Security as offline & Communication Cost. Works on
the authentication password Packet loss ratio & latency.
of User and the guessing
message. attack and
Diffie-Helman impersonation
protocol; smart attack
cards; hash
functions;
centralized trusted
authority for
loading smart-cards
with login id and
password
2016 [50] Obtains the real Authentication Improved In 60-70% of the cases the identity
identities of the results shown is correctly obtained.
drivers through t he on the real
Spanish eICards map during
the simulation
4. Conclusion & Future Scope
Researchers have been working intensely on improving the security mechanism in V2V communication and
have proposed various techniques as discussed in this survey. By comparing the work accomplished till date
some open issues have been discovered which can be used as a potential input for the future researchers. Firstly,
all the cluster based algorithms have been proved to be better than other techniques but the researchers must
keep on comparing their work within the domain with other cluster based algorithms. Also, it is assumed that
the real time environment has the RSUs and other infrastructure in place which is not the reality. The design
complexities while implementation should not be ignored. Apart from Firefly and Cuckoo, spline and
polynomial fit could be used for better comparison and improved results. There are very less impressions of
researches using IoT in this domain, so that’s another prospering field. Implementation of Elliptic Curve
cryptography in future to stimulate the identification process to work on location based mechanism is yet
another unexplored area. These are few areas where the future researches can be directed and help in achieving
the real time solutions.
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In this survey we discussed about various algorithms focusing on Secure and Authenticated algorithm under
four categories namely Clustering Based, Fog Based, ID Based and Smart Card Based. Towards the end we
shared some uncovered topics for future work with a hope that these issues are addressed by the researchers and
a potential solution is proposed.
Table 6: Abbreviations
DLIES Discrete Logarithm Integrated Encryption Scheme
DoS Denial of Service
SNI Smart & Normal Intrusions
PDR Packet Delivery Ratio
PIR Packet Injection Ratio
VFC VANET-cloud and fog computing
HDSA Hybrid DoS Attacks
ABC Artificial Bee Colony
LTP Long Term Pseudonym
STP Short Term Pseudonym
LTP Long Term Key
STK Short Term Key
TA Trusted Authority
RSU Road Side Unit
FFBPNN Feed forward back propagation neural network
VFC Vehicular Fog Computing
VANET Vehicular Ad-hoc Network
CBLR Cluster Based Location Routing
CPPA Conditional Privacy-Preserving Authentication
PAAVE Protocol for Anonymous
Authentication in Vehicular Networks (PAAVE)
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