Protecting Location Privacy with Clustering Anonymization in vehicular networks

Abstract

Location privacy is an important issue in location-based services. A large number of location cloaking algorithms have been proposed for protecting location privacy of users. However, these algorithms cannot be used in vehicular networks due to constrained vehicular mobility. In this paper, we propose a new method named Protecting Location Privacy with Clustering Anonymization (PLPCA) for location-based services in vehicular networks. This PLPCA algorithm starts with a road network transforming to an edge-cluster graph in order to conceal road information and traffic information, and then provides a cloaking algorithm based on A-anonymity and l-diversity as privacy metrics to further enclose a target vehicle's location. Simulation analysis shows our PLPCA has good performances like the strength of hiding of road information & traffic information.