Blockchain and Edge Intelligence-based Secure and Trusted V2V Framework Underlying 6G Networks

There is a significant rise in vehicle-to-vehicle (V2V) communication for intelligent transportation systems such as reducing road accidents, traffic congestion, and optimal route planning. The main objective of the V2V communication is to provide real-time monitoring data from vehicles sensors to other vehicles. However, the attackers can exploit this communication by forging the controller area network (CAN) protocol and injecting malicious traffic. In this context, the vehicles mislead by false update messages and alerts. To overcome this issue, this paper presents the artificial intelligence (AI) and blockchain-based proposed architecture on a 6G network. The proposed architecture is examined with a car hacking dataset, wherein the sensors of vehicles are communicating with each other for data sharing. For that, we have adopted an AI algorithm, i.e., random forest (RF), to classify normal and malicious data traffic. Further, edge nodes are considered to reduce the computation of AI algorithms and faster accessibility of vehicular data. Furthermore, incorporating inter planetary file system (IPFS) and a 6G network makes the proposed architecture cost-effective and scalable. Finally, the architecture is evaluated against performance metrics such as accuracy, latency, and scalability. The results demonstrate that the RF surpasses the other algorithms in terms of accuracy and achieves 97% accuracy.