Triggered query with strong location privacy in mobile network

Abstract

Location privacy is a hot-button topic that has to be taken into account if location-based services (LBS) are to succeed. Extensive researches focus on the nearest neighbor (NN) query or k-nearest neighbor (kNN) query about location privacy-preserving. However, no single technique can be applied to any situation and achieve high security and low cost. This manuscript focuses on the location privacy-preserving in the geo-fencing services, A secure two-party computation location privacy model and the corresponding solution was proposes based on triggered query. The author draw on the computational geometry and cryptography technologies, mainly to conquer such problems related to the users' location hidden, secret checking-in and secret authentication in the geo-fencing services. Performance assessment shows that the proposed solution can reduce the query-processing time and the size of query result set.