BIBRM: A Bayesian Inference Based Road Message Trust Model in Vehicular Ad Hoc Networks

Road congestion has troubled hundreds of thousands of drivers for a long time. In recent years, an application named dynamic routing, in which vehicles reroute themselves around congested areas with road information received, is proposed to deal with traffic jam. Due to lack of trust for road information in vehicular ad hoc networks (VANETs), malicious vehicles can easily disseminate false road information and mislead other vehicles to choose the wrong route. This paper proposes a new data centric trust model for road message in VANETs, which is based on data trust rather than entity trust to verify road messages, and utilizes Bayesian Inference in voting algorithm to increase robustness. Simulation results show that our model avoids malicious fake road messages and effectively improves the vehicle´s travelling time performance without additional message exchange.