A Transformer-Based Trust Management System for the Internet of Vehicles Using Blockchain Technology

In the Internet of Vehicles (IoV), the vehicular network serves as an open environment for information exchange, which makes it susceptible to internal attacks and leads to security concerns. Trust among vehicles plays a crucial role in addressing these challenges. However, previous approaches to trust management lack precision in evaluating vehicle trust, which limits their effectiveness in countering internal attacks within the vehicular network. To accurately assess the trust among vehicles, mitigate the spread of malicious messages, and prevent interference from malicious nodes within the vehicular network, this paper proposes TrustFormer, a trust management system based on Transformer. TrustFormer employs a transformer-based message detection model (TrMD) to detect each message in real time, converting it into a change in vehicle trust value. In addition, roadside units (RSUs) utilize blockchain technology to store the global trust values of vehicles, thereby ensuring their authenticity. Simulation results demonstrate that the proposed method outperforms existing approaches in terms of Precision, Recall, and F1-score against Bad Mouth Attack (BMA) and Zigzag Attack (ZA). Even with an increased number of malicious nodes in the network, the proposed method exhibits significant advantages, with less degradation in performance metrics compared to existing methods. Furthermore, blockchain performance simulation experiments indicate that the system latency meets the requirements of vehicular network applications, and throughput tests confirm its scalability.