A new K-NN query processing algorithm enhancing privacy protection in location-based services

Location-Based Services (LBSs) are becoming popular due to the advances in mobile networks and positioning capabilities. When a user sends a query with his exact location to the LBS server, the server processes the query and returns Points of Interest (POIs) to the user. Providing user's exact location to the LBS server may lead revealing his private information to unauthorized parties (e.g., adversaries). There exist two main fields of research to overcome this problem. They are cloaking region based query processing method which blurs a user's location into a cloaking region and Private Information Retrieval (PIR) based query processing methods which encrypt location data by using PIR protocol. However, they suffer from high computation and communication overheads. To resolve these problems, we, in this paper, propose a hybrid scheme to process an approximate k-Nearest Neighbor (k-NN) query by combining above two methods. Through performance analysis, we have shown that our hybrid scheme outperforms the existing work in terms of both query processing time and accuracy of the result set.