Evaluating the impact of adversarial traffic patterns on vanet communication using veins simulation

Abstract:Vehicular Ad Hoc Networks (VANETs) are a key component of intelligent transportation systems, enabling real-time communication between vehicles. However, their open and dynamic nature makes them highly vulnerable to adversarial behaviors that can disrupt communication reliability. This paper investigates the impact of adversarial traffic patterns on VANET performance using the Veins simulation framework integrated with OMNeT++ and SUMO. We design and evaluate multiple adversarial scenarios, including message flooding, false information dissemination, and coordinated congestion attacks, under varying traffic densities and mobility conditions. The study measures key performance metrics such as packet delivery ratio (PDR), end-to-end delay, and network throughput. Experimental results show that adversarial traffic can reduce PDR by up to 96.55%, with message flooding at low density producing a throughput reduction of 27.89%, and significantly degrade overall network efficiency. The findings highlight critical vulnerabilities in VANET communication and provide insights into designing more resilient and secure vehicular networks.

Networking and Internet Architecture (cs.NI); Machine Learning (cs.LG)

arXiv:2608.14583 [cs.NI]

(or arXiv:2608.14583v1 [cs.NI] for this version)

https://doi.org/10.48550/arXiv.2608.14583 Focus to learn more arXiv-issued DOI via DataCite

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