LPPS-AGC: Location Privacy Protection Strategy Based on Alt-Geohash Coding in Location-Based Services

The Internet of Things (IoT) connects billions of physical devices around the world to the Internet to collect and share massive data. Location privacy leakage has received considerable attention in the field of security. In order to implement the k-anonymity location privacy protection mechanism, a previous work constructed an anonymous location set by retrieving historical request record database from the trusted third anonymous server, which advantageously protects user's location privacy. However, the performance of location-based services (LBSs) is weakened by the time overhead of continual retrieving database. Moreover, with the increasingly flourishing of the positioning technique, user location can be accurate to the user's altitude beyond the two-dimensional latitude and longitude coordinates. In this paper, we present a location privacy protection strategy in LBSs based on Alt-Geohash coding (LPP-AGC) method synthetically considering the altitude of user location and time overhead. Specifically, we give the Alt-Geohash coding algorithm (AGCA) to retrieve the historical request record database, which greatly reduces the time overhead and ensures the immediacy of LBSs. In addition, we propose the dummy location generating algorithm (DLGA) and location filtering algorithm (LFA) to provide users with autonomous k-anonymity location privacy protection. Extensive simulations are performed to verify the performance and security of the proposed strategy.