Mobility Pattern Based Misbehavior Detection to Avoid Collision in Vehicular Adhoc Networks

Abstract

Vehicular Ad-hoc Network (VANET) can improve road safety through collision avoidance. False or bogus information is a real threat in VANET’s safety applications. Vehicles or drivers may react to false information and cause serious problems. In VANETs drivers’ behavioral tendencies can be reflected in the mobility patterns of the vehicles. Monitoring mobility patterns of the vehicles within their transmission range helps them in earlier detection of the correctness of the received message. This paper presents a misbehavior detection scheme (MDS) and corresponding framework based on the mobility patterns analysis of the vehicles in the vicinity of concerned vehicles. Initial simulation results demonstrate the potential of the proposed MDS and framework in message’s correctness detection, hence its corresponding applications in collision avoidance.