A Secure and Efficient Privacy-Preserving Range Query Scheme in Location-Based Services

Abstract

With the rapid development of wireless communications and mobile devices with location capability, location-based services (LBS) have been extensively used in almost all social and business domains. In terms of privacy and efficiency, there are two main limitations in the existing work that have to be addressed. First, they fail to preserve the location and content privacy simultaneously. Second, they do not support the range queries. In this paper, we propose a secure and efficient privacy-preserving range query protocol in the LBS, which satisfies the three requirements of the location privacy and content privacy protection, query efficiency, and scalable index size. To achieve location privacy and content privacy, we adopt the prefix membership verification scheme to encode index elements and a bloom filter to store index elements. To achieve query efficiency and scalable index size, a balanced dynamic binary tree structure called $DBtree$ is proposed. Furthermore, to improve the query efficiency, we propose both the index element encoding optimization and traversal optimization algorithms. Finally, we evaluate our scheme both on the simulated and real-world datasets. The experimental results demonstrate the security and efficiency of our scheme.