Research On Trajectory Privacy Protecting Method In LBS

As the development of mobile computing and sensor network, Location Based Service (LBS) is applied widely in recent years. User's location privacy receives more and more attention. Trajectory privacy protection is an important issue in LBS. Researchers proposed a lot of algorithms and ideas that are used to protect the location information. The existing methods are mostly involved in cutting the relationship between user's consecutive location information included in the queries. These methods make it difficult to get the trajectory for the attackers and can effectively protect user's trajectory privacy information to a certain extent.For the problems above, this paper propose BFQ(Based on Forwarding Queries) which is a trajectory privacy protecting method in a Peer-to-Peer (P2P) system. BFQ introduces two essential algorithms:1)Hilbert space-filling curve is used to map the 2-D locations of mobile users into 1-D space. The transformed locations are indexed and ordered to form a Hilbert sequence.2) The Chord distributed protocol is used to organize the orderd mobile users into a P2P system. The P2P system is a Chord ring which includes all mobile users who wants to receive LBS. Every user belongs to a cluster in which has 3 a (system parameter) users. There are cluster heads and their successors and predecessors on the Chord ring. The information of the cluster members is maintained by the cluster head. When a user issues a query, his cluster head notifies every cluster members to initiats theκ-Anonimity Spatial Area(κ-ASR) construction process. Ifκusers are not found in the cluster, the cluster head will issue a request for the nodes in his predecessor list or sucessor list. Then theκ-ASR and the Minimum Boundary Rectangle(MBR) which contains the anonimity sets are formed. Finally the successor or predecessor of the cluster head is selected to forward the queries to LBS.The experiments are conducted to show that BFQ outperforms MOBIHIDE in abilities of resisting the center-of-k-ASR attack and the correlation attack, the operation of mobile users'joining and departuring the system and system load balancing. BFQ makes it difficult to get the source queries and location information for attackers when users update their queries continuously. Therefore it can protect the user's trajectory privacy effectively.