A Historical Feedback Based Misbehavior Detection (HFMD) Algorithm in VANET

Abstract

Vehicular Ad-hoc Network (VANET) is a promising technology with a great potential for providing enhanced safety and convenience to the drivers and passengers. The majority of application in VANET involves exchange of information amongst vehicles. An adversary may take this as an advantage to disturb the network by disseminating false information about any occurred event on the road. In this paper, we propose a Historical Feedback based Misbehavior Detection Algorithm (HFMDA) to detect the misbehavior vehicles inside from the network. In this algorithm, an observer vehicle sends a notification to the nearest RSU against a crash-event occurred on the road. Here we assume that all vehicles accumulate its past history for event notifications. All the vehicles maintains this history with two parameters: Event Notifications (EN) and True Event Notification (TEN). In proposed HFMD algorithm, a vehicle's historical record is firstly check to know its past misbehavior history and an RSU_Verification algorithm is used to verify the status of current received notification at the RSU. The proposed hybrid algorithm i.e. data centric and event centric, is a RSU side algorithm instead of vehicle side. The RSU overhead is significantly reduced through the proposed algorithm since verification of only highest trusted vehicle is done.