Securing Vehicular Networks Based on Data-Trust Computation

Vehicular ad-hoc networks (VANETs) have a great potential to improve road safety, traffic jams, fuel consumption, and to increase passenger convenience in vehicles. However, VANETs use an open medium for communication and, therefore, are exposed to security threats that influence their reliability. We propose a data-trust security model designed for VANETs based on social network theories. Drivers receiving data about traffic congestion or safety warnings can use the model to evaluate the trust in the received information. The model computes a trust index for each message based on the relevance of the event. It also uses a gossiping approach to disseminate data-trust indexes between vehicles, increasing the accuracy in the trustworthiness of an event and assuring the privacy by hiding the original event sources. The approach is evaluated through modeling and simulation, and we present results that proof its validity.