BTDS:Blockchain-Enabled Trusted Vehicle Violation Detection by Self-Supervision

In recent years, the accelerated advancement of Internet of Vehicles (IoV) technology has significantly enhanced user experiences by providing intelligent services such as multimedia entertainment and autonomous driving in vehicles. However, the enforcement of regulations concerning vehicle violations in IoV environments predominantly relies on manual methods, which are both expensive and challenging. Moreover, the inherent constraints in existing surveillance systems result in regulatory blind spots. Consequently, it is imperative to develop intelligent IoV-based surveillance mechanisms to improve the efficiency of detecting and rectifying violations. In this paper, we propose a blockchain-based self-supervision model for vehicle violations that utilizes inter-vehicle reporting and voting mechanisms to enhance the detection rate of violations and reduce regulatory pressure. A forensic blockchain is introduced in the model to enable a review of the reporting results, which improves the security and reliability of the system. Additionally, more vehicles are incentivized to participate in the system through reputation-based rewards, punishments, and incentives. The system was deployed on the Hyperledger Fabric platform. Simulation experiments were conducted using Veins, SUMO, and OMNeT++. The experimental results verify the effectiveness of the model. The reporting and voting mechanism significantly inhibit violations, and the reward and reputation mechanism effectively promote the participation of vehicles.