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Safeguarding connected autonomous vehicle communication: Protocols, intra- and inter-vehicular attacks and defenses

2025-02-06 · Mohammed Aledhari, Rehma Razzak, Mohamed Rahouti, Abbas Yazdinejad, Reza M. Parizi, Basheer Qolomany, Mohsen Guizani, Junaid Qadir, Ala Al-Fuqaha

The advancements in autonomous driving technology, coupled with the growing interest from automotive manufacturers and tech companies, suggest a rising adoption of Connected Autonomous Vehicles (CAVs) in the near future. Despite some evidence of higher accident rates in AVs, these incidents tend to result in less severe injuries compared to traditional vehicles due to cooperative safety measures. However, the increased complexity of CAV systems exposes them to significant security vulnerabilities, potentially compromising their performance and communication integrity. This paper contributes by presenting a detailed analysis of existing security frameworks and protocols, focusing on intra- and inter-vehicle communications. We systematically evaluate the effectiveness of these frameworks in addressing known vulnerabilities and propose a set of best practices for enhancing CAV communication security. The paper also provides a comprehensive taxonomy of attack vectors in CAV ecosystems and suggests future research directions for designing more robust security mechanisms. Our key contributions include the development of a new classification system for CAV security threats, the proposal of practical security protocols, and the introduction of use cases that demonstrate how these protocols can be integrated into real-world CAV applications. These insights are crucial for advancing secure CAV adoption and ensuring the safe integration of autonomous vehicles into intelligent transportation systems.

📄 PDF Abstract BibTeX arXiv:2502.04201

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Autonomous DrivingAutonomous Vehicles

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SET Dynamic Sparse Training method where weight mask is updated randomly periodically

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