Privacy-Preserving Location-Based Query Over Encrypted Data in Outsourced Environment

Abstract

The location-based services in the outsourced environment has become a research hotspot with the rise of cloud computing. Meanwhile, various privacy issues have been increasingly prominent. We propose an efficient spatial query protocol and another novel secure spatial query protocol using fully homomorphic encryption to accomplish privacy-preserving query processing on outsourced data. We adopt the Moore curve to transform the spatial data into one-dimensional sequence and utilize the random permutation to protect the location privacy. Furthermore, the proposed efficient scheme provides the considerable performance with data privacy preservation. Meanwhile, the secure spatial query protocol is robust against various attacks. Experiments show that the proposed schemes achieve high accuracy while improving the security when compared with the existing related approaches.