Location Privacy Preservation Mechanism for Location-Based Service With Incomplete Location Data

Abstract

The Location-Based Service has been widely used for mobile communication networks and location systems. However, privacy disclosure for incomplete collection location data in LBS was ignored in most of the existing works. To solve the problem of privacy disclosure, we propose a location privacy method based k-anonymity to prevent privacy disclosure in LBS constrained in incomplete data collection. The proposed scheme can provide effectively location privacy-preserving in the process of constructing the anonymous set, and against background attacks. In this method, we first designed a construct method for anonymous candidate set(ACS) with compressing sensing technology, to solve the problem of incomplete data of collection location. To prevent the privacy disclosure in the process of construct anonymous, we then adapt the differential privacy mechanism to construct the anonymous set(AS) with the ACS. we finally used the optimization method based on the Stackelberg game model to improve the privacy level of AS to against probabilistic attack. As shown in the theoretical analysis and the experimental results, the proposed method can achieve significant improvements in terms of privacy degree and applicability.