DMTAS-VB: Dynamic Model Update-based Trust Assessment Strategy for VANETs Considering Blockchain

As one of the most critical aspects of mobile ad hoc networks, vehicular ad hoc networks (VANETs) have attracted increasing attention with the growing demand for safety in transportation systems. Trust assessment is crucial in VANETs, as it can effectively identify and mitigate the impact of malicious vehicles, thereby ensuring the reliability and security of network communication. However, the models in most existing trust schemes cannot be dynamically updated over time, failing to adapt to the high dynamics of VANETs. Moreover, they lack protection for data privacy, increasing the risk of information tampering and leakage. To solve the above problems, this paper proposes a new Dynamic Model Update-based Trust Assessment Strategy for VANETs Considering Blockchain (DMTAS-VB). Specifically, DMTAS-VB addresses two primary aspects. Firstly, with respect to the dynamic model, the trust framework proposed in this study incorporates both direct trust and recommended trust models that are dynamically updated as interactions progress. Secondly, regarding privacy protection, blockchain is introduced into the trust model of this scheme. The innovative three-chain structure (MainBC, MesBC, and RepBC) is adopted to achieve functional separation, and core identity authentication, high-frequency message exchange, and reputation management are handled independently. The system can more flexibly optimize the performance parameters of each chain while enhancing data security and privacy protection. Simulation results demonstrate that the proposed scheme outperforms comparative approaches in detection performance under various conditions (vehicle number, vehicle speed, proportion of malicious vehicles) and different attack modes (SA, ZA, BMA, BA, and CA).