Authentication protocols in internet of vehicles: Taxonomy, analysis, and challenges
Open accessAbstract
Internet of Vehicles (IoV) is treated as an extension of Vehicle-to-Vehicle (V2V) communication network. IoV helps in enhancing driving aids with the help of vehicle Artificial Intelligence (AI) awareness of other vehicles and their actions. IoV is connected in an adhoc networking environment which utilizes each vehicle in the network as a node, called Vehicular Ad Hoc Network (VANET), where the vehicles may be also connected to the public Internet. It is specifically important for the autonomous vehicles because they can instantaneously communicate with other vehicles surrounding them. In addition, safely avoiding accident prone zones is crucial in order to continue secure and smart transportation. Since the communication among various entities involved in the IoV environment is via open channel, it gives an opportunity to a passive/active adversary to intercept, modify, delete or even insert fake information during communication. It is then a serious concern for the vehicles users to determine whether the received information is genuine. In this survey paper, various security aspects, threats and attacks, network and threat models related to the IoV environment are discussed. Next, a taxonomy of security protocols is given that is essential to provide IoV data security. In particular, focus on various authentication protocols is given that is needed for mutual authentication among the involved entities in the IoV environment for secure communication. A detailed comparative analysis among various state-of-art authentication protocols proposed in the related IoV environment is provided to show their effectiveness as well as security and functionality features. Moreover, some testbeds are described that were designed and implemented for the IoV environment. In addition, some future challenges for IoV security protocols are also highlighted that are necessary to address in the future.
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IoV is vulnerable to multiple threats, and researchers have identified some of the most vulnerable areas and how they can be protected from network attacks.
“While IoV is vulnerable to multiple threats, researchers have identified some of the most vulnerable areas and how they can be protected from network attacks [57,58,59,60].”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [59]
Malicious attacks are initiated with intent to harm participating nodes, are dangerous, and can cause significant damage.
“With malicious attacks, rather than attackers benefiting from the attacks, they are instead initiated with the intent of harming participating nodes. These attacks are dangerous and can cause significant damage.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [59]
Malicious attackers can transmit false safety-critical information that puts drivers, passengers, and pedestrians in danger.
“Malicious attackers can even transmit false safety-critical information that puts drivers, passengers, and pedestrians in danger [59,78,102,103,104].”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [59]
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- Authors
- Bagga, P., Das, A. K., Wazid, M., Rodrigues, J. J. P. C., & Park, Y.
- Affiliations
- International Institute of Information Technology, Hyderabad (IN)
- Graphic Era University (IN)
- Universidade Federal do Piauí (BR)
- Kyungpook National University (KR)
- Venue
- IEEE Access
- Published
- 2020
- Volume
- 8
- Pages
- 54314-54344
- ISSN
- 2169-3536 (ISSN-L)
- OpenAlex
- W3010998992
- Cited by
- 168
- References
- 6
- Citations by year
- 2026: 18 · 2025: 20 · 2024: 53 · 2023: 18 · 2022: 32 · 2021: 18 · 2020: 9
- FWCI
- 6.61
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- IEEE Access (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Research Foundation of Korea (2017R1A2B1002147)
- BK21 Plus project funded by the Ministry of Education, South Korea (21A20131600011)
- FCT/MCTES through national funds and when applicable co-funded EU funds (UIDB/EEA/50008/2020)
- Brazilian National Council for Scientific and Technological Development (309335/2017-5)
- Ripple Centre of Excellence Scheme, CoE in Blockchain, IIIT Hyderabad, India, IIIT/Research and Development Office/Internal (Projects/001/2019)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Computer Networks and Communications › Advanced Authentication Protocols Security
- Physical Sciences › Engineering › Mechanical Engineering › IoT and GPS-based Vehicle Safety Systems
- Keywords
- Internet of Vehicles, authentication protocols, vehicular ad hoc networks, mutual authentication, VANET security, vehicle-to-vehicle communication, autonomous vehicles, threat model, protocol taxonomy, vehicular communication security, testbed
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