Collaborative caching techniques for privacy-preserving location-based services in peer-to-peer environments

Abstract

The number of users who uses location-based services (LBS) which utilize a user's location information to provide beneficial services has been increasing rapidly along with the proliferation of mobile devices such as the smartphone. However, LBS users have expressed concerns regarding their privacy because the collected location information can bring about privacy violations if used maliciously by the LBS provider. Thus, developing privacy-preserving techniques to prevent the exposure of the user's location information is important for the wide application of LBS. Consequently, many researches are being conducted on topics such as location k-anonymity and pseudonym to prevent privacy threats. However, existing research is difficult to apply in real-world LBS because of several limitations such as additional computation and legacy system change cost. In this paper, we propose a P2P architecture to protect the user's location privacy in LBS using personal data storage (PDS) to overcome the drawback in existing techniques. We also introduce a collaborative caching technique, which shares extra query results among users to mitigate performance degradation, that is, for preserving location privacy. Simulation results show that the proposed technique achieves sufficient privacy protection without a trusted third party for anonymization while minimizing system performance degradation.