Sybil Attack Detection Algorithm for Internet of Vehicles Security

In the context of traffic congestion and traffic accidents that seriously threaten people’s safety, vehicle networking, through the connection between vehicles, enables vehicles to effectively obtain traffic environment information, which is considered as an effective way to solve traffic safety problems. However, as a complex network, there are some security risks in the Internet of vehicles. This paper focuses on Sybil attack detection algorithm for Internet of vehicles security, aiming to make full use of vehicle perception data, communication data, user data, etc. in the Internet of vehicles to eliminate specific security risks and curb malicious behaviors. To be specific, first of all, a data-driven security architecture for Internet of vehicles is proposed. Secondly, aiming at the possible Sybil attack in ride-hailing applications, Sybil attacks in Internet of vehicles are divided into three levels according to the different capabilities of attackers, and different detection methods are designed and modeled according to their different characteristics. Finally, a solution based on mobile behavior analysis is proposed.