PPT-LBS: Privacy-preserving top-k query scheme for outsourced data of location-based services

Abstract

Location-based service (LBS) is enjoying a great popularity with the fast growth of mobile Internet. As the volume of data increases dramatically, an increasing number of location service providers (LSPs) are moving LBS data to cloud platforms for benefit of affordability and stability. However, while cloud server provides convenience and stability, it also leads to data security and user privacy leakage. Aiming at the problems of insufficient privacy protection and inefficient query in the existing LBS data outsourcing schemes, this paper presents a novel privacy-preserving top-k query for outsourcing situations. Firstly, to ensure data security of LSP and privacy of the user, the enhanced asymmetric scalar-product preserving encryption and public key searchable encryption have been adopted to encrypt outsourced data and LBS query, which can effectively lower the computational cost and realize the privacy protection search. Secondly, an efficient and secure index structure is constructed by using a coded quadtree and the bloom filter, so that the cloud server can quickly locate the user’s query region to improve retrieval efficiency. Finally, the formal security analysis is given under the random oracle model, and the performance is evaluated by experiments which demonstrates that our scheme is preferable to existing schemes.