A Robust Detection of the Sybil Attack in Urban VANETs

The Sybil attack is one of the serious attacks to vehicular ad hoc networks (VANETs), because it severely damages the security of VANETs and, even leads to a threat to lives of drivers and passengers. In this paper, we propose a solution to detect the Sybil attack based on the differences between the normal motion trajectories of vehicles and the abnormal ones. In our approach, each node can accomplish the attack detection independently with the limited assistance from the infrastructures of VANETs. We improve the feasibility of our approach with limited infrastructures at the early deployment stages of VANETs. In addition, the independency and feasibility of our algorithm are more robust than the existing solutions that rely on collaboration of neighboring nodes. Simulation results show that the proposed method outperforms the existing solutions in terms of robustness, detection rate, overhead efficiency, and lower system requirements.