CT2‐MDS: Cooperative trust‐aware tolerant misbehaviour detection system for connected and automated vehicles - Ying Liu; Hongwei Xue; Weichao Zhuang; Fa'an Wang; Liwei Xu; Guodong Yin (IET Intelligent Transport Systems, 2022)
Abstract Connected and automated vehicles (CAVs) are recognized as a promising solution to improve road safety. Before deploying CAVs, securing the communication environment is a critical challenge. To secure the exchanged sensitive messages between CAVs, a novel cooperative trust‐aware tolerant misbehaviour detection system (CT2‐MDS) is proposed in this paper. The vehicle‐to‐everything (V2X) network model in real complex scenarios is built first, and several typical types of attacks are simulated. The cooperative trust factor is then defined to evaluate the received message packet's plausibility instead of the node. And the measuring uncertainty of sensors is considered to improve the overall detection precision. At last, a multi‐model fusion misbehaviour detection method is presented based on the idea of cross‐validation. In this mechanism, different from the binary classification, the misbehaviour messages are categorized into particular misbehaving classes. To verify the proposed system's performance, the simulation is conducted, and the results showed that the proposed method outperformed existing single classifiers and provided good prediction accuracy in different attack density.