Sybil Attack Detection in Vehicular Ad-hoc Networks using Direct Trust Calculation

Abstract

Vehicular Ad-hoc Networks (VANETs) are gaining rapid momentum with the increasing number of vehicles on the road. VANETs are ad-hoc networks where vehicles exchange information about the traffic, road conditions to each other or to the road-side infrastructures. VANETs are characterized by high mobility and dynamic topology changes due to the high-speed vehicles in the network. These characteristics pose security challenges as vehicles can be conceded. It is critical to address security for the sake of protecting private data of vehicle and to avoid flooding of false data which defeats the purpose of VANETs. Sybil attack is one of the attacks where a vehicle fakes multiple vehicle identity to compromise the whole network. In this work, a direct trust manager is introduced which derives the trust value of each of its neighbor nodes at a regular interval of time. If the trust value is deviated, it confirms sybil attack. The proposed system is compared with the existing system to prove improved sybil attack detection ratio, thus providing better security. NS2 environment is used to prove the simulation results. The experimental results show that the attack detection ratio of SAD-V-DTC is 5 times better than that of the existing system. The packet delivery ratio shows an improvement of 27.27% while the false positive shows a good increase of 65.80% than the existing system.