Decentralized Reputation Model based on Bayes' Theorem in Vehicular Networks

Vehicular Ad hoc Network (VANET) is a wireless technology dedicated to vehicular communications. VANET is unsecure because of its lack of central administration and is also vulnerable due to its unique characteristics. Therefore, security is one of the most critical issues in this type of network. For a high level of safety, we need a method to evaluate vehicular communications' trust and measure nodes' reliability. This article presents a decentralized reputation model, where the activity of each node (i.e., vehicle) is observable for adjacent nodes. Our model enables nodes to detect malicious vehicles and avoids interacting with them. We propose to use the Bayesian filter to measure the trust scores of vehicles accurately. Different from conventional trust models, we study the concept of classification and misclassification. We then analyze the accuracy of our Bayesian filter by computing the factors of Node Recall and Node Precision. The extensive simulations have shown that the proposed filter can assign an accurate trust score to nodes under various network conditions and misbehavior rates.