A Survey on Vehicular Ad hoc Networks Security Attacks and Countermeasures
Open accessAbstract
Vehicular Ad hoc Networks (VANETs), a subcategory of Mobile ad hoc networks (MANETs), is a promising approach that is now evolving, gaining attention and momentum. VANET consists of highly mobile nodes and roadside infrastructure to communicate essential information across a network, such as collisions, traffic congestion, and vehicular destinations. Due to its frequent vehicle movement, time-critical response and hybrid architecture, it comes with a plethora of network security and privacy issues ranging from the potential of malicious attacks to the availability of essential information across the network and its overall integrity. There is much research devoted to enabling secure communication in VANETs for the best Intelligent Transport System (ITS) experience. In this paper, we address and discuss the characteristics and security issues including the existing VANETs attacks and preventive approaches to each security attack emphasising the main features and the major drawbacks. The review of these different countermeasures shows their strengths and weaknesses and how they can be implemented independently or in a hybrid model best suited to the situation.
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[72] discussed security challenges in vehicular networks with emphasis on attacks and preventive measures, but without explicit mentions of machine learning or trust.
“In [72], the security challenges within vehicular networks are discussed primarily, with an emphasis on attacks and preventive measures, but without explicit mentions of machine learning or trust.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [72]
Despite several surveys on IoV security, few surveys have covered ML-based solutions in security or trust schemes in this environment.
“Despite the fact that there are several surveys on IoV security [12,65,67,69,71,72,73,74,75], few surveys have covered ML-based solutions in security or in trust schemes in this environment.”
From Security and Trust Management in the Internet of Vehicles (IoV): Challenges and Machine Learning Solutions (2024) · cites this paper as [72]
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References 25 · Cited by 3
- Authors
- Abuarqoub, A., Alzu'bi, A., Hammoudeh, M., Ahmad, A., & Al-Shargabi, B.
- Affiliations
- Cardiff Metropolitan University (GB)
- Department of Computer Science, Jordan University of Science and Technology, Jordan
- King Fahd University of Petroleum and Minerals (SA)
- Middle East University (JO)
- Venue
- Proceedings of the 6th International Conference on Future Networks & Distributed Systems
- Publisher
- ACM
- Published
- 2022-12-15
- Pages
- 701-707
- OpenAlex
- W4376055814
- Cited by
- 3
- References
- 25
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 1
- FWCI
- 0.81
- Type
- conference paper
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- International Conference on Future Networks and Distributed Systems (ICFNDS) (publishedVersion)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
- Physical Sciences › Computer Science › Computer Networks and Communications › Security in Wireless Sensor Networks
- Physical Sciences › Engineering › Control and Systems Engineering › Smart Grid Security and Resilience
- Keywords
- vehicular ad hoc networks, VANET security, security attacks, attack countermeasures, privacy, intelligent transportation systems, mobile ad hoc networks, roadside infrastructure, secure communication
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