ClusterRep: A cluster-based reputation framework for balancing privacy and trust in vehicular participatory sensing

Abstract

In vehicular participatory sensing, vehicles may provide false data or low-quality data. Building trust in vehicular ad hoc networks is an efficient way to deal with this issue. On one hand, vehicles need to disclose necessary information to demonstrate their trustworthiness. On the other hand, vehicles tend to hide their sensitive information to preserve user privacy. Therefore, privacy and trust are conflict in vehicular ad hoc networks. A cluster-based reputation framework named ClusterRep is proposed to balance privacy and trust in vehicular ad hoc networks. In this framework, the cluster head collaborates with cluster members to change pseudonyms and reputation values. The experiments show the scalability and the effectiveness of the ClusterRep compared with Beta strategy and IncogniSense-floor strategy.