Vehicular ad-hoc networks (VANETs) allow communication among vehicles using some fixed equipment on roads called roads side units. Vehicular communications are used for sharing different kinds of information between vehicles and RSUs in order to improve road safety and provide travelers comfort using exchanged messages. However, falsified or modified messages can be transmitted that affect the performance of the whole network and cause bad situations in roads. To mitigate this problem, trust management can be used in VANET and can be distributive for ensuring safe and secure communication between vehicles. Trust is a security concept that has attracted the interest of many researchers and used to build confident relations among vehicles. Hence, the authors propose a secured clustering mechanism for messages exchange in VANET in order to organize vehicles into clusters based on vehicles velocity, then CH computes the credibility of message using the reputation of vehicles and the miner controls the vehicle's behavior for verifying the correctness of the message.
A Machine Learning System for Routing Decision-Making in Urban Vehicular Ad Hoc Networks