Privacy Preserving Towards Continuous Query in Location-Based Services

With advances in wireless communication and mobile positioning technologies, location-based mobile services have been gaining increasingly popularity in recent years. Privacy preservation, including location privacy and query privacy, has recently received considerable attention for location-based mobile services. A lot of location cloaking approaches have been proposed for protecting the location privacy of mobile users. However, they mostly focus on anonymizing snapshot queries based on proximity of locations at query issued time. Therefore, most of them are ill-suited for continuous queries. In view of the privacy disclosure (including location and query privacy) and poor quality of service under continuous query anonymization, a δp-privacy model and a δq-distortion model are proposed to balance the tradeoff between privacy preserving and quality of service. Meanwhile a temporal distortion model is proposed to measure the location information loss during a time interval, and it is mapped to a temporal similar distance between two queries. Finally, a greedy cloaking algorithm (GCA) is proposed, which is applicable to both anonymizing snapshot queries and continuous queries. Average cloaking success rate, cloaking time, processing time and anonymization cost for successful requests are evaluated with increasing privacy level (k). Experimental results validate the efficiency and effectiveness of the proposed algorithm.