Preserving Location and Content Privacy for Secure Ranked Queries in Location Based Services
Pei Chen, Yaping Lin, Wei Zhang, Xiaoying Li, Shiwen Zhang · 2016
The Location-Based Services (LBSs) have attracted a lot of attention in recent years. For privacy concerns, there are abundant works focusing on the secure query over the location server. However, these works suffer from two main limitations. First, they cannot preserve the location privacy and content privacy simultaneously during LBS queries. Second, they do not support the ranked queries. In this paper, we aim to propose a ranked and fine-grained query protocol in the LBSs, while preserving both the location privacy and content privacy. To prevent the location server from knowing the exact location of the query users, we propose to hidetheir location data in a concealing disk. To prevent the location server from deducing the content of query data, we systematically construct a secure query protocol, where different data providers can use different secret keys to encrypt their data, the query users can query over these data securely and efficiently. To prevent the location server from launching the statistical attacks, we propose to "fuzzify" the query data for each query operation. Furthermore, we devise a ranked and fined-grained query protocol, which is compatible with the widely used search algorithms. Finally, we give rigorous security analysis and conduct extensive experiments, which confirms the efficacy and efficiency of our proposed scheme.