Evaluating the Impact of DoS Attacks on Connected and Autonomous Vehicle Traffic Flow with Car-following Theory

This paper aims to assess the impact of denial-of-service (DoS) attacks on the traffic flow of connected and autono-mous vehicles (CAVs). With this aim, a novel car-following model is presented to depict the dynamics of CAVs to support a compre-hensive analysis of the CAV traffic performance. Particularly, the model uniquely integrates the information delay, the optimal ve-locity changes with memory and the malicious effect of manipu-lated information. Then, the linear stability of the proposed model is derived using the perturbation method. By introducing small perturbations into the system, the stability conditions for a platoon of CAVs are determined. Finally, extensive simulations are con-ducted to explore the impact of DoS attack on CAV traffic. Our experimental results demonstrate that the model accurately captures real traffic flow, particularly the behavior of a CAV platoon under a DoS network attack.