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Review

Security in V2I Communications: A Systematic Literature Review

Departamento de Informática y Ciencias de la Computación, Escuela Politécnica Nacional, Ladrón de Guevara E11-25 y Andalucía, Edificio de Sistemas, Quito 170525, Ecuador
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Author to whom correspondence should be addressed.
Sensors 2022, 22(23), 9123; https://doi.org/10.3390/s22239123
Received: 8 October 2022 / Revised: 18 November 2022 / Accepted: 18 November 2022 / Published: 24 November 2022
(This article belongs to the Special Issue Data Privacy, Security, and Trust in New Technological Trends)

Abstract

:
Recently, the number of vehicles equipped with wireless connections has increased considerably. The impact of that growth in areas such as telecommunications, infotainment, and automatic driving is enormous. More and more drivers want to be part of a vehicular network, despite the implications or risks that, for instance, the openness of wireless communications, its dynamic topology, and its considerable size may bring. Undoubtedly, this trend is because of the benefits the vehicular network can offer. Generally, a vehicular network has two modes of communication (V2I and V2V). The advantage of V2I over V2V is roadside units’ high computational and transmission power, which assures the functioning of early warning and driving guidance services. This paper aims to discover the principal vulnerabilities and challenges in V2I communications, the tools and methods to mitigate those vulnerabilities, the evaluation metrics to measure the effectiveness of those tools and methods, and based on those metrics, the methods or tools that provide the best results. Researchers have identified the non-resistance to attacks, the regular updating and exposure of keys, and the high dependence on certification authorities as main vulnerabilities. Thus, the authors found schemes resistant to attacks, authentication schemes, privacy protection models, and intrusion detection and prevention systems. Of the solutions for providing security analyzed in this review, the authors determined that most of them use metrics such as computational cost and communication overhead to measure their performance. Additionally, they determined that the solutions that use emerging technologies such as fog/edge/cloud computing present better results than the rest. Finally, they established that the principal challenge in V2I communication is to protect and dispose of a safe and reliable communication channel to avoid adversaries taking control of the medium.

1. Introduction

According to Statista [1], by 2021, the number of connected vehicles worldwide will reach 237 million units, and by 2025 that number will be 400 million. The impact of those numbers in the telecommunication area is enormous. One of the implications is related to security in communications. Because of the opening of wireless communications, the dynamic topology and the big size of the network, and the use of the same credentials for registration, attackers may be able to listen, forge, manipulate, or destroy information exchanged between vehicles and roadside units affecting the proper operation and performance of the network [2,3,4].
Generally, there are two modes of communication in a vehicular network: Vehicle to Infrastructure (V2I) and Vehicle to Vehicle (V2V). This last one has the advantage of having roadside units (RSU) with high computational and transmission power to exchange information at high speed with vehicles. For instance, it assures the correct operation of driving guidance and early warning services. In addition to the advantages of V2I, benefits such as avoiding traffic accidents or traffic jams or accessing services on the Internet could justify why many authors have focused more on V2I communication than V2V [2,3]. In that way, it is also essential to cover some aspects of security in this type of communication.
This literature review aims to report the most current and relevant information on V2I communications security. In that way, the authors posed five research questions. The first one is related to the vulnerabilities in this type of communication and their respective countermeasures. The second concerns the methods, technologies, tools, or mechanisms used to provide security solutions to mitigate these vulnerabilities. The third and fourth ones are about the available evaluation metrics to measure the effectiveness of the solutions and thus find out which offers the best results. Finally, the last one concerns the challenges to be faced by the proposals and their possible solutions.
One of the contributions of the present review is the information that the authors provided compared to previous studies related to the same topic. The authors noted that almost all reviews focus on all communication in Vehicular Ad-hoc Network (VANET) without emphasizing V2I communication. VANET is a large overall system model comprising four approaches comprehending driver and vehicle, traffic flow, communications, and applications. The components related to data communication are V2V and V2I. The whole system is vast and complex. Therefore, this research aims to provide a systematic literature review centered on one of the components of VANET: V2I communication, to review it in more detail.
The rest of this article is organized as follows: Section 2 presents the definitions of specific attacks, evaluation metrics, and methods. Meanwhile, Section 3 presents the methodology used to elaborate on this review. Then, Section 4 shows the information used to answer the research questions, followed by Section 5, which introduces the answers to those questions and discusses the most relevant security aspects of V2I. Finally, the conclusions of this work are presented in Section 6.

2. Concepts and Definitions

Section 2.1 and Section 2.2 present the lists of the security requirements and attacks that occur in V2I communications. Section 2.3 presents a list of evaluation metrics used by the authors, and Section 2.4 the main methods used to provide solutions.

2.1. Security Requirements

  • Confidentiality: It guarantees that only authorized nodes can access and reveal sensitive information.
  • Integrity: It ensures that the information sent by the sender is the same as that received by the receiver.
  • Authentication: It guarantees that the node that wants to access or use network resources is who it claims to be.
  • Availability: It ensures that the access to network resources for authorized nodes is continuous and without interruptions.
  • Non-repudiation: It guarantees that neither the receiver nor the sender can deny having processed certain information.

2.2. Attacks

  • MitM: It occurs when an adversary secretly enters the communication of two devices to make them believe that they are communicating directly and thus exchange its public key between the devices.
  • Replay: It occurs when an adversary listens to the communication, intercepts it, and later fraudulently resend the obtained messages.
  • Modification/Tampering: It occurs when an adversary alters the message transmitted between two nodes fraudulently.
  • DoS: It occurs when an adversary floods the communication system with no genuine requests getting the service down.
  • Repudiation: It occurs when a system or application does not track nor log the user’s actions properly, permitting manipulation or forging new actions.
  • Session Key Disclosure: It occurs when an adversary can obtain values from memory devices (OBU or TPD) and messages from insecure communication channels. Thus, the adversary can calculate the session key using the values and messages.
  • Impersonation: It occurs when an adversary can take someone’s identity to gain advantages or cause damage to other nodes.
  • Sybil: It occurs when an adversary forges node identities to obtain privileges and thus causes chaos in normal conditions.
  • Forgery: It occurs when an adversary forges a valid certificate and signs a message successfully.
  • Bogus: It occurs when an adversary generates a fake node in a network and informs it about false traffic conditions in a particular location.
  • Eavesdropping: It occurs when an adversary listens to the communication channel extracting information that can be useful for node tracking activity.
  • Plaintext: It occurs when an adversary, who has access to the ciphertext and its plaintext, tries to guess the secret key or develops an algorithm for decrypting messages.
  • Key Leakage: It occurs when an adversary, who has access to the signer, can learn some sensitive information (e.g., computation-time, memory contents, and others).
  • Chosen Message: It occurs when an adversary, who can obtain the ciphertext of plaintext messages from the signer, tries to reveal the secret encryption key.
  • Ciphertext: It occurs when an adversary, who has access to a set of ciphertexts, tries to guess the plaintexts or even the key.
  • Beacon Transmission Denial: It occurs when an adversary suspends itself its beacon transmission for an indefinite time to avoid detection.

2.3. Evaluation Metrics

  • Computational Cost: It refers to the time required to apply certain operations to a message before sending it over the network.
  • Communication Overhead: It refers to the length of information transmitted by a successful message transference.
  • Transmission Delay: It refers to the time a packet takes to get to the destination from the source.
  • Propagation Delay: It refers to the distance between the sender and receiver divided by the light speed.
  • Packet Delivery Ratio: It refers to the ratio of packets successfully delivered to their destinations.
  • Packet Loss Ratio: It refers to the ratio between the number of lost packets and the total number of sent packets.
  • Accuracy: It refers to the general ratio of vehicles correctly detected.
  • Trust Value: It refers to the general cooperativeness of a user.
  • Data Receiving Rate: It refers to the rate of data successfully received.
  • Storage Cost: It refers to the memory size required to store the parameters in the different devices.
  • Roaming Latency: It refers to the time required to transfer the node control between gateways.
  • Cyphertext Length: It refers to the length of messages after performing encryption operations.
  • Energy Consumption: It refers to the energy consumed during the routing process.
  • Throughput: It refers to the rate of messages successfully transmitted in one second over a communication channel.
  • Attack Detection Ratio: It refers to the ratio between the number of attacks detected and the total number of attacks.
  • Average Delay: It refers to the expected time a beacon message of a node remains in a queue before being sent to the infrastructure.
  • False Accept Ratio: It refers to the ratio between the correct number of planned trajectories and the total number of trajectories of a node.

2.4. Methods

  • Elliptic Curve Cryptography (ECC): It is a public key encryption technique that generates cryptographic keys using the elliptic curve theory.
  • Public Key Cryptography (PKC): It is a scheme that performs encryption and decryption using public and private keys. The public key is published, and the private one is kept secret. It is known as asymmetric key cryptography.
  • Symmetric Key Cryptography (SKC): It is a cryptography scheme that uses the same key for encryption and decryption.
  • Public Key Infrastructure (PKI): It is a scheme in which the public key is associated with a certificate provided by a certificate authority instead of choosing one generated randomly.
  • Identity-Based Public Key Cryptography (IBPKC): It is a scheme that uses a representation of identity as the public key to avoid using public ones associated with a certificate. Instead of a certificate authority, there is a key generation center to generate the private keys based on the public ones.
  • Certificateless-Based Cryptography (CBC): It is a scheme that distributes the private keys of the key generation center into several entities. In this scheme, the user and the key generation center calculate the private key, but only the user can obtain the result.

3. Materials and Methods

The authors used Kitchenham’s guide [5,6] for performing systematic reviews to elaborate on this work. Thus, they considered the following phases and activities: Planning the Review-Research Questions, Conducting the Review-Search Strategy, Study Quality Assessment, and Data Extraction, and Reporting the Review-Results.

3.1. Planning the Review

The five research questions for this review are presented as follows.
  • RQ01. What are the principal vulnerabilities in V2I communications?
  • RQ02. What are the methods or tools to mitigate those vulnerabilities?
  • RQ03: What evaluation metrics are available to measure the effectiveness of those methods or tools?
  • RQ04: What methods, technologies, or tools provide the best results based on those evaluation metrics?
  • RQ05: What are the principal challenges for mitigating vulnerabilities in VANETs?

3.2. Conducting the Review

3.2.1. Search Strategy

The authors used the following bibliographic databases: IEEExplore, ACM Digital Library, and Semantic Scholar. From the research questions, they extracted the following keywords: VANET, V2I, privacy, authentication, confidentiality, and integrity. They developed the search strings using the keywords, the meaning of acronyms VANET and V2I, and the operators AND and OR. Table 1 presents the search strings, date filters, and the search results.

3.2.2. Study Selection

They established some inclusion and exclusion criteria to accomplish the study selection process.
  • Inclusion Criteria
    IC01. Studies that are peer-reviewed research papers.
    IC02. Studies published in the last five years.
    IC03. Studies published in journals and conferences.
  • Exclusion Criteria
    EC01. Studies that are literature reviews, chapters in books, analysis papers, comparative papers, position papers, theses, technical reports, workshop reports, or lecture notes.
    EC02. Studies published in preprint platforms.
    EC03. The full text of the study is not available.

3.2.3. Quality Assessment

The authors defined one assessment question and established two possible answers for each one. The questions are presented as follows. The answer “no” is rated with 0 and “yes” with 1.
  • AQ01. Is the study targeted at V2I communications?
They established that the primary study is accepted only if the score is equals to 1; otherwise, it will be rejected. Table A1 presents the quality instrument and its results. As can be seen in Figure 1, 430 articles were found after performing the search. Of them, 48 duplicates were removed, for a total of 382. Then, 335 were removed because they did not meet the inclusion and exclusion criteria, for a total of 47. After that, 11 articles obtained on the snowballing technique were added, for a total of 58. Finally, 11 articles were removed because they did not fulfill the quality criterion. Thus, the selected articles reached 47. Table A2 presents the selected primary studies.

3.2.4. Data Extraction

The authors designed three data collection forms to obtain information from the selected primary studies. The following is a description of each of them. Firstly, Table 2 includes the primary study ID and the attacks to which the proposal is resistant. Whereas Table 3 contains the primary study ID, the category to which it belongs, and the methods, technologies, simulators, and other tools on which the solutions are based. Finally, Table 4 contains the primary study ID and the evaluation metrics used by the proposals. The design of those tables was based on addressing the research questions. Thus, they used Table 2 to answer RQ01, Table 3 to answer RQ02, and Table 4 to answer both RQ03 and RQ04. The generated data are presented in Section 3 and interpreted in Section 4.

3.3. Reporting the Review

Of 47 primary studies, 21 are from conferences, and 26 are from journals. The two years when more studies have been published are 2018 and 2019. Figure 2 shows the number of studies and types published by year.

4. Results

The authors determined that around seven of every ten solutions use a simulation as an experimental method and around one of every ten solutions as an experiment. Furthermore, they found that one of every two solutions uses network simulators, and one of every two uses both network and traffic simulators. Figure 3 presents the experimental methods and the use of simulators.

4.1. Data Collections Forms

The three data collection forms (Table 2, Table 3 and Table 4) described in the Data Extraction are presented as follows. Table 2 presents the attacks to which the proposals are resistant. Table 3 presents the methods, technologies, and tools used to provide solutions. Table 4 presents the evaluation metrics used to measure the effectiveness of the proposals.

4.2. Review of Reviews

Intending to contribute more to this topic, the authors performed a simplified review of reviews. Similarly, they used the same search strategy and partly the study selection presented in this section. Below, the authors present two data collection forms (Table 5 and Table 6) with all the information extracted from the reviews.

5. Discussion

The answers to the five research questions are presented as follows.
RQ01: What are the principal vulnerabilities in V2I communications?
Since wireless communications are easy to intercept, the principal vulnerability in this type of communication is the susceptibility to attacks. Thus, adversaries can compromise RSUs/vehicles and send false information to drivers putting their lives at risk. They can also send unnecessary alerts to distract them and control the communication links. Once it is done, the adversaries can easily modify session messages. Considering that fact, researchers have focused on proposing solutions that offer any attack resistance. From the results, the authors identified the attacks to which the solutions are resistant. They found the following attacks: MitM, Replay, Tampering, DoS, Repudiation, Session Key Disclosure, Impersonation, Sybil, Forgery, Eavesdropping, and Plaintext. The authors commonly offer solutions against Replay, Impersonation, MitM, Tampering, and Sybil attacks.
RQ02: What methods, technologies, or tools can mitigate those vulnerabilities?
The proposals were grouped using the following categories. The Network Communication Security category for routing protocols, communication schemes, messages exchange security, and privacy protection; the Malicious Node Detection category for intrusion detection systems, trust management schemes, and intrusion prevention systems; and the Authentication Scheme category. According to Figure 4, eight of every ten proposals are about Authentication Schemes, one is about Network Communication Security, and less than one is about Malicious Node Detection.
Regarding technologies, The authors observed that there are several solutions based on PKC/ECC with Blockchain. This technology is gaining attentions in various study fields. This interest must be due to its key features such as decentralization, anonymity, and immutability [46,47]. Regarding simulators, authors have used both network and traffic ones. Figure 5 presents the use of simulators in studies based on the frequency of occurrence. According to it, they use OMNeT++, NS-3, and NS-2 to a greater extent and Veins, SSGA, and MOVE to a lesser extent, and the only traffic simulator is SUMO.
RQ03: What evaluation metrics are available to measure the effectiveness of those methods or tools?
Researchers have used the following evaluation metrics to measure the performance of their solutions. Metrics such as computational cost/time/overhead, communication cost/overhead, storage cost/overhead, transmission delay, propagation delay, packet delivery ratio, packet drop ratio, accuracy, trust value, data receiving rate, roaming latency, cyphertext length, energy consumption, and false success rate. The more common metrics in order of occurrence are computational cost, communication overhead, transmission delay, and packet delivery rate. Because of the use of emerging technologies to solve certain obstacles and limitations, more researchers are focusing on evaluation metrics such as computational cost and communication overhead to measure the effectiveness of their solutions.
RQ04: What methods, technologies, or tools provide the best results based on those evaluation metrics?
From the results, the authors could establish that the solutions that offer better results are the ones in which the use of emerging technologies to overcome certain limits and obstacles are present. Thus, considering metrics such as computational cost and overhead, the solutions based on Fog/Edge/Cloud computing present better results than the others. The following comparative analysis (Table 7) reinforces this assumption.
From the main methods (Figure 6), there is a slight trend of using Elliptic Curve Cryptography (ECC) instead of traditional cryptography (PKC); however, the evaluation metrics present good results for both cases. In this case, it is necessary for further research to determine the best method based on the evaluation metrics. Apart from the methods, researchers have also used network and traffic simulators, map tools, security tools, programming languages, platforms, and libraries. Figure 7 presents the distribution of the tools used in the proposals. The most used map tool is Open Street. About security tools, the most common are MIRACL and Avispa. The most used programming languages are C and Python, and among libraries, OpenSSL.
RQ05: What are the principal challenges for mitigating vulnerabilities in VANETs?
Since vehicles with limited computing resources must interact with communication infrastructure at high speed, the great challenge in vehicular networks is to dispose of a safe and reliable communication channel and suitable device performance. When a vehicle enters the coverage of a new roadside unit, the computational overhead can lower the quality of communications and driving safety. Not all attacks in vehicular networks are protected with security mechanisms such as cryptography techniques, digital signatures, or message verification technique, and there are others as the bogus attack that requires a solution. Counting with a secure channel to transmit authentication information is still a paradigm considering that some security schemes must be applied to resource-limited and time-critical devices.

6. Conclusions and Future Work

The capacity of modern vehicles to connect to an external infrastructure makes them vulnerable to cyber-attacks. Counting with a secure channel to transmit authentication information is still a paradigm considering that some security schemes must be applied to resource-limited and time-critical devices. V2I communications offer more advantages and benefits to users than V2V communications. Hence, the reasons for studying the state-of-the-art of security in V2I communications.
In the present review, the authors found that the principal attacks to which solutions are resistant are multiple and varied. The attackers could intrude on a network to intercept and manipulate the messages using MitM, Replay, Repudiation, Eavesdropping, or Tampering; shut down a machine making it inaccessible with DoS; pretend to be someone else to access information through impersonation and Sybil attack; tricks a web browser into executing unwanted actions using Forgery; obtain the key with plaintext attacks where the attacker knows the plaintext and its corresponding encrypted ciphertext or with Exploitation of the session control mechanisms with Session Key disclosure; among others fraudulent techniques.
Diverse methods and tools are developed to mitigate these vulnerabilities. They grouped them into solutions for authentication/trust management/network communication schemes for privacy preserving, IDS and IPS models to alert and act over a security incident, and routing protocol management to protect the devices. To evaluate the effectiveness of the methods and tools used to mitigate the vulnerabilities that measure computational cost through communication overhead, transmission delay, and data delivery reliability. The authors observed that researchers must address their future work toward using emerging technologies to reduce computational overhead and save computational costs. They observed a slight trend in using ECC instead of traditional cryptography. However, it is too soon to establish if ECC will become the dominant choice in cryptography in a few years. What is certain is that the use of emerging technologies such as Fog/Edge/Cloud computing, Cloudlets, Blockchain, Software-Defined Networking, and Network Functions Virtualization has suffered a rapid expansion. In fact, the inclusion of emerging technologies in proposals has contributed to reducing the computational overhead and saving the computational costs.
After conducting a simplified review of reviews, the authors observed that the number of analyzed articles in almost all reviews is insufficient, and the lack of a search strategy is surprising. The reviews vaguely mentioned evaluation metrics and emerging technologies as possible solutions to overcome certain limitations. Concerning the methods used to build solutions, the other authors mentioned at least the most common ones. Finally, the list of threats/attacks proposed in the reviews is relatively small compared to the list in the present review.
On the other hand, the authors identified coincidences in the presentation of information on fundamentals, security requirements, threats/attacks, solutions, and challenges. However, the present review stands out because it presents, for instance, a comparative analysis of emerging technologies in relation to some performance metrics, some graphics related to the percentage of occurrence in solutions of the methods, tools, and simulators used by researchers to build solutions against vulnerabilities, and also one representing the percentage of occurrence about the types of solutions presented in the present review. Not to mention the valuable information the authors obtained from a review of review articles.

Author Contributions

Conceptualization, P.M.; methodology, P.M. and D.T.-U.; investigation, P.M. and D.T.-U.; writing—original draft preparation, P.M.; writing—review and editing, P.M., Á.L.V.C., and M.H.-Á.; supervision, Á.L.V.C. and M.H.-Á. All authors have read and agreed to the published version of the manuscript.

Funding

The publication of this research was funded by the Research and Social Projection Department of Escuela Politécnica Nacional.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Acknowledgments

Our recognition to the Research and Social Projection Department of Escuela Politécnica Nacional.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

Appendix A

Table A1. Quality instrument.
Table A1. Quality instrument.
TitleScore
A Blockchain-Assisted Seamless Handover Authentication for V2I Communication in 5G Wireless Networks1
A blockchain-based certificateless public key signature scheme for vehicle-to-infrastructure communication in VANETs1
A lightweight Privacy-Preserving V2I Mutual Authentication Scheme using Cuckoo Filter in VANETs1
A low computation message delivery and authentication VANET protocol1
A privacy-preservation framework based on biometrics blockchain (BBC) to prevent attacks in VANET1
A Secure Blockchain-Based Group Mobility Management Scheme in VANETs1
A Security Model for Intelligent Vehicles and Smart Traffic Infrastructure0
A Strong Secure V2I Authentication Scheme from PKI and Accumulator1
A Traceable Blockchain-Based Access Authentication System With Privacy Preservation in VANETs1
A Traceable Concurrent Data Anonymous Transmission Scheme for Heterogeneous VANETs1
A trust infrastructure based authentication method for clustered vehicular ad hoc networks1
An Efficient and Anonymous Authentication Key Agreement Protocol for Smart Transportation System1
An efficient V2I authentication scheme for VANETs1
An Improved Secure and Efficient Certificateless Conditional Privacy-Preserving Authentication Scheme in VANETs1
B-TSCA: Blockchain Assisted Trustworthiness Scalable Computation for V2I Authentication in VANETs1
Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks1
CIAS: A comprehensive identity authentication scheme for providing security in VANET1
Continuous authentication for VANET1
Cybersecurity Attacks in Vehicle-to-Infrastructure Applications and Their Prevention1
Decentralized and Scalable Privacy-Preserving Authentication Scheme in VANETs1
Design of Blockchain-Based Lightweight V2I Handover Authentication Protocol for VANET1
Detection of Beacon Transmission Denial Attack in ITS Using Temporal Auto-Correlation and Random Inspections1
Dynamic Defense Strategy Against DoS Attacks Over Vehicular Ad Hoc Networks Based on Port Hopping1
ECCHSC: Computationally and Bandwidth Efficient ECC-Based Hybrid Signcryption Protocol for Secure Heterogeneous Vehicle-to-Infrastructure Communications1
eCLAS: An Efficient Pairing-Free Certificateless Aggregate Signature for Secure VANET Communication1
Enhancing Beaconing Efficiency via Grouping for Vehicular Communications1
Formal Validation of a Security Mechanism against the RSU Compromise Attack0
Get in Line: Ongoing Co-presence Verification of a Vehicle Formation Based on Driving Trajectories1
HDMA: Hybrid D2D Message Authentication Scheme for 5G-Enabled VANETs1
IFAL: Issue First Activate Later Certificates for V2X0
Improved Dual Authentication and Key Management Techniques in Vehicular Ad Hoc Networks1
LCPPA: Lattice-based conditional privacy preserving authentication in vehicular communication1
Low-Latency Secure Roaming in V2I Networks1
LSWBVM: A lightweight security without using batch verification method scheme for a vehicle ad hoc network1
LVAP: Lightweight V2I authentication protocol using group communication in VANETs1
Machine learning approach for detecting location spoofing in VANET0
MComIoV: Secure and Energy-Efficient Message Communication Protocols for Internet of Vehicles1
Persistent Traffic Measurement Through Vehicle-to-Infrastructure Communications0
Physical Layer Key Generation: Securing Wireless Communication in Automotive Cyber-Physical Systems0
PLVA: privacy-preserving and lightweight V2I authentication protocol1
Practical V2I Secure Communication Schemes for Heterogeneous VANETs1
Privacy-preserving authentication scheme with full aggregation in VANET1
Privacy-preserving vehicular rogue node detection scheme for fog computing1
Proven secure tree-based authenticated key agreement for securing V2V and V2I communications in VANETs1
Pseudo-identity Based Secure Communication Scheme for Vehicular Ad-hoc Networks1
Reputation Based Traffic Event Validation and Vehicle Authentication using Blockchain Technology1
Roadside Unit Allocation for Fog-Based Information Sharing in Vehicular Networks0
SecProtobuf: Implicit Message Integrity Provision in Heterogeneous Vehicular Systems0
Secure Communication Protocol for Smart Transportation Based on Vehicular Cloud1
Secure Data Streaming to Untrusted Road Side Units in Intelligent Transportation System1
Secure V2V and V2I Communication in Intelligent Transportation using Cloudlets1
Securing V2X Communications for the Future: Can PKI Systems Offer the Answer?0
Smart Certificate Revocation List Exchange in VANET0
Strong privacy preserving authentication scheme for unmanned cars1
Token-based lightweight authentication scheme for vehicle to infrastructure communications1
Track me if you can? Query based dual location privacy in VANETs for V2V and V2I1
Trust-Based Distributed Authentication Method for Collision Attack Avoidance in VANETs0
Verification Based Authentication Scheme for Bogus Attacks in VANETs for Secure Communication1
Table A2. Primary studies.
Table A2. Primary studies.
IDAuthorsTitleYearType
PS01Yu et al. [48]A Blockchain-Assisted Seamless Handover Authentication for V2I Communication in 5G Wireless Networks2021Conference
PS02Ali et al. [49]A blockchain-based certificateless public key signature scheme for vehicle-to-infrastructure communication in VANETs2019Journal
PS03Moni et al. [50]A lightweight Privacy-Preserving V2I Mutual Authentication Scheme using Cuckoo Filter in VANETs2022Conference
PS04Ahmed et al. [51]A low computation message delivery and authentication VANET protocol2017Conference
PS05Alharthi et al. [52]A privacy-preservation framework based on biometrics blockchain (BBC) to prevent attacks in VANET2021Journal
PS06Lai et al. [53]A Secure Blockchain-Based Group Mobility Management Scheme in VANETs2019Conference
PS07Heng et al. [54]A Strong Secure V2I Authentication Scheme from PKI and Accumulator2022Conference
PS08Zheng et al. [55]A Traceable Blockchain-Based Access Authentication System With Privacy Preservation in VANETs2019Journal
PS09Liu et al. [56]A Traceable Concurrent Data Anonymous Transmission Scheme for Heterogeneous VANETs2018Conference
PS10Mirsadeghi et al. [57]A trust infrastructure based authentication method for clustered vehicular ad hoc networks2021Journal
PS11Jagriti et al. [58]An Efficient and Anonymous Authentication Key Agreement Protocol for Smart Transportation System2021Conference
PS12Zhou et al. [59]An efficient V2I authentication scheme for VANETs2018Journal
PS13Wang et al. [60]An Improved Secure and Efficient Certificateless Conditional Privacy-Preserving Authentication Scheme in VANETs2020Conference
PS14Wang et al. [61]B-TSCA: Blockchain Assisted Trustworthiness Scalable Computation for V2I Authentication in VANETs2020Journal
PS15Hathal et al. [62]Certificateless and Lightweight Authentication Scheme for Vehicular Communication Networks2020Journal
PS16Malik et al. [63]CIAS: A comprehensive identity authentication scheme for providing security in VANET2018Journal
PS17Palaniswamy et al. [64]Continuous authentication for VANET2020Journal
PS18Islam et al. [65]Cybersecurity Attacks in Vehicle-to-Infrastructure Applications and Their Prevention2018Journal
PS19Tangade et al. [66]Decentralized and Scalable Privacy-Preserving Authentication Scheme in VANETs2018Journal
PS20Son et al. [67]Design of Blockchain-Based Lightweight V2I Handover Authentication Protocol for VANET2022Journal
PS21Sultana et al. [68]Detection of Beacon Transmission Denial Attack in ITS Using Temporal Auto-Correlation and Random Inspections2019Conference
PS22Jie et al. [69]Dynamic Defense Strategy Against DoS Attacks Over Vehicular Ad Hoc Networks Based on Port Hopping2018Journal
PS23Ali et al. [70]ECCHSC: Computationally and Bandwidth Efficient ECC-Based Hybrid Signcryption Protocol for Secure Heterogeneous Vehicle-to-Infrastructure Communications2021Journal
PS24Han et al. [71]eCLAS: An Efficient Pairing-Free Certificateless Aggregate Signature for Secure VANET Communication2021Journal
PS25Feng et al. [72]Enhancing Beaconing Efficiency via Grouping for Vehicular Communications2019Conference
PS26Vaas et al. [73]Get in Line: Ongoing Co-presence Verification of a Vehicle Formation Based on Driving Trajectories2018Conference
PS27Wang et al. [74]HDMA: Hybrid D2D Message Authentication Scheme for 5G-Enabled VANETs2020Journal
PS28Rekik et al. [75]Improved Dual Authentication and Key Management Techniques in Vehicular Ad Hoc Networks2017Conference
PS29Dharminder et al. [76]LCPPA: Lattice-based conditional privacy preserving authentication in vehicular communication2021Journal
PS30Richa et al. [77]Low-Latency Secure Roaming in V2I Networks2018Conference
PS31Al-Shareeda et al. [78]LSWBVM: A lightweight security without using batch verification method scheme for a vehicle ad hoc network2020Journal
PS32Liu et al. [79]LVAP: Lightweight V2I authentication protocol using group communication in VANETs2017Journal
PS33Limbasiya et al. [80]MComIoV: Secure and Energy-Efficient Message Communication Protocols for Internet of Vehicles2021Journal
PS34Lv et al. [81]PLVA: privacy-preserving and lightweight V2I authentication protocol2021Journal
PS35Zhou et al. [2]Practical V2I Secure Communication Schemes for Heterogeneous VANETs2019Journal
PS36Zhong et al. [82]Privacy-preserving authentication scheme with full aggregation in VANET2019Journal
PS37Al-Otaibi et al. [83]Privacy-preserving vehicular rogue node detection scheme for fog computing2019Journal
PS38Wei et al. [84]Proven secure tree-based authenticated key agreement for securing V2V and V2I communications in VANETs2021Journal
PS39Singh et al. [85]Pseudo-identity Based Secure Communication Scheme for Vehicular Ad-hoc Networks2019Conference
PS40Al-Ali et al. [86]Reputation Based Traffic Event Validation and Vehicle Authentication using Blockchain Technology2020Conference
PS41Limbasiya et al. [87]Secure Communication Protocol for Smart Transportation Based on Vehicular Cloud2019Conference
PS42Jolfaei et al. [88]Secure Data Streaming to Untrusted Road Side Units in Intelligent Transportation System2019Conference
PS43Gupta et al. [89]Secure V2V and V2I Communication in Intelligent Transportation using Cloudlets2020Conference
PS44Jeon et al. [90]Strong privacy preserving authentication scheme for unmanned cars2018Conference
PS45Hathal et al. [91]Token-based lightweight authentication scheme for vehicle to infrastructure communications2019Conference
PS46Arif et al. [92]Track me if you can? Query based dual location privacy in VANETs for V2V and V2I2018Journal
PS47Celes et al. [93]Verification Based Authentication Scheme for Bogus Attacks in VANETs for Secure Communication2018Conference

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Figure 1. The review process.
Figure 1. The review process.
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Figure 2. Primary studies published by year and type of publication.
Figure 2. Primary studies published by year and type of publication.
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Figure 3. Experimental methods and use of simulators based on the frequency of occurrence.
Figure 3. Experimental methods and use of simulators based on the frequency of occurrence.
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Figure 4. Types of solutions based on the frequency of occurrence.
Figure 4. Types of solutions based on the frequency of occurrence.
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Figure 5. Use of network simulators based on the frequency of occurrence.
Figure 5. Use of network simulators based on the frequency of occurrence.
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Figure 6. Use of methods based on the frequency of occurrence.
Figure 6. Use of methods based on the frequency of occurrence.
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Figure 7. Use of tools based on the frequency of occurrence.
Figure 7. Use of tools based on the frequency of occurrence.
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Table 1. Search Results.
Table 1. Search Results.
Database Search EngineIDCommand SearchDate FiltersSearch DateTotal
ScopusSS01((“All Metadata”:”vehicular ad hoc network” OR “All Metadata”:vanet) AND (“All Metadata”:”vehicle to infrastructure” OR “All Metadata”:v2i) AND “All Metadata”:security AND (“All Metadata”:privacy OR “All Metadata”:authentication OR “All Metadata”:confidentiality OR “All Metadata”:integrity))2017–202222 June 202255
SS02((“All Metadata”:”vehicle to infrastructure” OR “All Metadata”:v2i) AND “All Metadata”:security AND (“All Metadata”:privacy OR “All Metadata”:authentication OR “All Metadata":confidentiality OR “All Metadata”:integrity))2017–202222 June 202296
151
ACMSS03[[All: “vehicular ad hoc networks”] OR [All: vanet]] AND [[All: “vehicle to infrastructure”] OR [All: v2i]] AND [All: security] AND [[All: privacy] OR [All: authentication] OR [All: confidentiality] OR [All: integrity]][Publication Date: Past 5 years]22 June 202267
SS04[[All: “vehicle to infrastructure”] OR [All: v2i]] AND [All: security] AND [[All: privacy] OR [All: authentication] OR [All: confidentiality] OR [All: integrity]][Publication Date: Past 5 years]22 June 2022152
219
Semantic ScholarSS05vanet vehicular ad-hoc network v2i vehicle to infrastructure privacy authentication confidentiality integrityLast 5 years22 June 202240
SS06v2i vehicle to infrastructure privacy authentication confidentiality integrityLast 5 years22 June 202220
60
Table 2. Protection against attacks.
Table 2. Protection against attacks.
IDMiTMReplayModificationTamperingDoSSession Key DisclosureImpersonationSybilForgeryBogusEavesdroppingPlaintextKey LeakageChosen MessageCiphertextBeacon Trans. Denial
PS01
PS02
PS03
PS04
PS05
PS06
PS07
PS08
PS09 *
PS10
PS11
PS12
PS13
PS14
PS15
PS16 *
PS17
PS18
PS19
PS20
PS21
PS22
PS23
PS24
PS25
PS26
PS27
PS28
PS29
PS30
PS31
PS32
PS33
PS34
PS35
PS36
PS37
PS38
PS39
PS40
PS41
PS42
PS43
PS44
PS45
PS46 *
PS47
* Not defined. √ Defined.
Table 3. Methods and tools.
Table 3. Methods and tools.
IDCategoryMethodsBased on TechnologySimulatorsOther Tools
PS01AuthenticationElliptic Curve Cryptography (ECC)BlockchainBouncy Castle [7] and Scyther Tool [8]
PS02AuthenticationCertificateless-Based Cryptography (CBC)BlockchainMIRACL [9]
PS03AuthenticationCuckoo filtersCrypto++ [10]
PS04AuthenticationPublic Key Cryptography (PKC) and Symmetric Key CryptographyNS-2 [11]
PS05Network SecurityIdentity-Based PKCBlockchainOMNeT++ [12] and SUMO [13]
PS06AuthenticationPublic Key Infrastructure (PKI) and ECCBlockchain
PS07AuthenticationPKCBlockchainCrypto++
PS08AuthenticationPKC and ECCBlockchainGo environment [14]
PS09AuthenticationPKC and Certificateless-Based CryptographyJava Pairing Based Cryptography (JPBC) library [15]
PS10AuthenticationPKC and Trust Degree EstimationMatlab [16]
PS11AuthenticationHash functions and XOR operations
PS12AuthenticationECC and Private Key InsulationTEPLA [17]
PS13AuthenticationCertificateless-Based Cryptography and ECCMIRACL
PS14AuthenticationPKCBlockchainGMP [18] and PBC [19] libraries
PS15AuthenticationCertificateless-Based CryptographyNS-3 [20] and SUMO
PS16AuthenticationPKCOMNeT++ and SUMO
PS17AuthenticationProtocols suiteOMNeT++ and SUMOTamarin [21], TEPLA [17], and Python Cryptography Tool (pycrypto) [22]
PS18Intrusion Prevention SystemEdge Computing, Software, Defined Networking (SDN) and Network Functions Virtualization (NFV)Stop Sign Gap Assist (SSGA) [23]
PS19AuthenticationIdentity-Based PKC and Hash Message Authentication Code (HMAC)NS-3 [20], SUMO, and MObility Model Generator for Vehicular Networks (MOVE) [24]
PS20AuthenticationBlockchainNS-3, Automated Validation of Security Protocols and Applications (AVISPA) [25]MIRACL and PBC
PS21Intrusion Detection SystemAuto Correlation Function (ACF)OMNeT++ and SUMO
PS22Network SecurityPort Hopping Technique
PS23AuthenticationPKC and Identity-Based PKCNS-2
PS24AuthenticationCertificateless-Based CryptographyMIRACL
PS25AuthenticationCooperative Group Beaconing Strategy
PS26AuthenticationProtocol Based on Vehicles TrajectoryOpen Street Map [26]
PS27AuthenticationIdentity-Based PKC and PseudonymsMIRACL and PBC
PS28AuthenticationPKCAVISPA and OpenSSL [27]
PS29AuthenticationLattice-Based Cryptosystem
PS30AuthenticationRoaming ProtocolOMNeT++
PS31AuthenticationECC, Identity-based PKC, and PseudonymsMIRACL
PS32AuthenticationSymmetric Encryption and Group Signature
PS33Communication ProtocolECC and One-Way Hash FunctionTestbed [28]
PS34AuthenticationBGN Homomorphic Encryption and Moore Curve Technique
PS35AuthenticationPKI and Identity-Based Cryptosystem (IBC)
PS36AuthenticationCertificateless Aggregate Signature and PseudonymsMIRACL
PS37AuthenticationSymmetric Key EncryptionFog Computing
PS38AuthenticationAuthenticated Key Agreement (AKA), ECC and Hash FunctionsOMNeT++, SUMO, and Veins [29]MIRACL and Crypto++
PS39AuthenticationIdentity-Based Cryptography
PS40AuthenticationReputation-Based ValidationBlockchainSocket.io [30], Node.js [31], and Google Maps [32]
PS41AuthenticationSymmetric and Asymmetric Cryptography, and ECCAVISPA and Proverif [33]
PS42Messages exchange securityPermutation-Only EncryptionGroup Formation Criteria
PS43Messages exchange securityCloudletsAWS IoT [34], AWS Greengrass [35], and Boto [36]
PS44AuthenticationPKI and Message Accessing Code (MAC) Encryption
PS45AuthenticationAuthentication Tokens and Schnorr SignatureNS-3 and SUMO
PS46Privacy ProtectionTrusted Third Party (TTP) and Circle Based Dummy Generation (CBDG)OMNeT++, SUMO, and Veins
PS47Intrusion Detection System (IDS)Position Verification TechniqueNS-2
✗ Not defined.
Table 4. Evaluation Metrics.
Table 4. Evaluation Metrics.
IDComputational CostCommunication OverheadTransmission DelayPropagation DelayPacket Delivery RatioPacket Loss RatioAccuracyTrust ValueData Receiving RateStorage CostStorage OverheadRoaming LatencyCyphertext LengthEnergy ConsumptionThroughputAttack Detection RateAverage DelayFalse Accept RateOthers
PS01
PS02
PS03
PS04
PS05
PS06
PS07
PS08
PS09
PS10
PS11
PS12
PS13
PS14
PS15
PS16
PS17
PS18
PS19
PS20
PS21
PS22
PS23
PS24
PS25
PS26
PS27
PS28
PS29
PS30
PS31
PS32
PS33
PS34
PS35
PS36
PS37
PS38
PS39
PS40
PS41 *
PS42
PS43
PS44 *
PS45
PS46
PS47
* Not defined. √ Defined.
Table 5. Review articles.
Table 5. Review articles.
IDAuthorsTitleAimSearch StrategyNumber of StudiesYear
RV01Islam et al. [37]A Comprehensive Survey on Attacks and Security Protocols for VANETsIt informs about fundamentals, application areas, security services, and possible attacks in vehicular networks.Not defined112021
RV02Hamdi et al. [38]A review on various security attacks in vehicular ad hoc networksIt discusses security concerns, security services, and advances in authentication. It also describes attacks and threats.Not defined132021
RV03Sheikh et al. [39]A Survey of Security Services, Attacks, and Applications for Vehicular Ad Hoc Networks (VANETs)It presents an overview of VANET that includes architecture, communication methods, standards, and characteristics. It also presents security services, security threats and attacks, simulation tools, and challenges.Not defined>652019
RV04Singh et al. [40]Advanced Security Attacks on Vehicular AD HOC Network (VANET)It presents security requirements, challenges, attacks, and privacy issues in VANET.Not definedNot defined2019
RV05Azam et al. [41]An outline of the security challenges in VANETIt informs about security attacks and solutions.Not defined62020
RV06Kohli et al. [42]Future Trends of Security and Privacy in Next Generation VANETIt addresses security and privacy issues in next-generation VANET. It also presents solutions for those issues.Not defined112020
RV07Mitsakis et al. [43]Recent Developments on Security and Privacy of V2V & V2I Communications: A Literature ReviewIt presents solutions to both the attacks and challenges in a VANET.Not defined152020
RV08Mihai et al. [44]Security Aspects of Communications in VANETsIt presents relevant proposals for privacy, authentication, and integrity in the context of vehicular networks.Not defined122020
RV09Goyal et al. [45]Security Attacks, Requirements, and Authentication Schemes in VANETIt provides a classification of attacks, security requirements, and authentication schemesNot defined82019
N/AOur reviewSecurity in V2I Communications: A Systematic Literature ReviewIt informs the principal vulnerabilities and challenges in V2I communications, the tools and methods to mitigate those vulnerabilities, the evaluation metrics to measure the effectiveness of those tools and methods, and based on those metrics, the methods or tools that provide the best results.Available472022
Table 6. Comparative analysis among reviews.
Table 6. Comparative analysis among reviews.
IDProtection against AttacksMethods and ToolsBased on TechnologySimulatorsEvaluation Metrics
RV01DoSPKI
TamperingECC
SybilIBPKC
Replay
Impersonation
RV02DoS Blockchain
Tampering
Impersonation
Sybil
Replay
Eavesdropping
MitM
RV03DoSPKCCloud computingSUMOComputational cost
TamperingSKC OMNET++Communication overhead
MitMIBPKC NS-2
EavesdroppingPKI NS-3
ImpersonationHash functions Veins
ReplayECC
Sybil
RV04Tampering
Impersonation
Sybil
MitM
DoS
Eavesdropping
Replay
Bogus
RV05DoSPKIBlockchain
TamperingHash functionsFog computing
Eavesdropping
Sybil
Replay
RV06DoSPKI
Bogus
Impersonation
Eavesdropping
RV07DoSPKI
SybilPKC
MitMSKC
Tampering
Impersonation
Replay
RV08MitMPKIBlockchain
ImpersonationIBPKC
Tampering
Eavesdropping
RV09TamperingPKI Computational cost
EavesdroppingECC Communication overhead
SKC Average delay
IBPKC
Our reviewMitMECCBlockchainSUMOComputational cost
ReplayCBCEdge computingOMNet++Communication overhead
ModificationPKISDNNS-3Transmission delay
TamperingPKCNFVNS-2Propagation delay
DoSSKCFog computingVeinsPacket Delivery Ratio
Session Key DisclosureIBPKCGroup Formation CriteriaSSGAPacket Loss Ratio
ImpersonationHash functionsCloud computingMOVEAccuracy
SybilPseudonyms Trust Value
Forgery Data Receiving Rate
Bogus Storage Cost
Eavesdropping Storage Overhead
Plaintext Roaming Latency
Key Leakage Cyphertext Length
Chosen Message Energy Consumption
Ciphertext Throughput
Beacon Transmission Denial Attack Detection Rate
Average Delay
False Accept Rate
Table 7. Comparative analysis of emerging technologies in relation to some performance metrics.
Table 7. Comparative analysis of emerging technologies in relation to some performance metrics.
BlockchainFogEdgeCloudCloudlets
Computing
LatencyLowMediumLowHighLow
ScalibilityLowHighHighMediumLow
Energy ConsumptionHighMediumLowHighMedium
InteroperabilityLowHighLowHighLow
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Marcillo, P.; Tamayo-Urgilés, D.; Valdivieso Caraguay, Á.L.; Hernández-Álvarez, M. Security in V2I Communications: A Systematic Literature Review. Sensors 2022, 22, 9123. https://doi.org/10.3390/s22239123

AMA Style

Marcillo P, Tamayo-Urgilés D, Valdivieso Caraguay ÁL, Hernández-Álvarez M. Security in V2I Communications: A Systematic Literature Review. Sensors. 2022; 22(23):9123. https://doi.org/10.3390/s22239123

Chicago/Turabian Style

Marcillo, Pablo, Diego Tamayo-Urgilés, Ángel Leonardo Valdivieso Caraguay, and Myriam Hernández-Álvarez. 2022. "Security in V2I Communications: A Systematic Literature Review" Sensors 22, no. 23: 9123. https://doi.org/10.3390/s22239123

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