Researches On Location Privacy Protection Based On Nearest Neighbor Queries

The nearest-neighbor queries as the most important way of the Location-based Service(LBS)makes people's life more convenient.Therefore,how to effectively protect personal location privacy has become an urgent problem to be solved.The thesis analyzes the advantages and disadvantages of existing location privacy protection technologies,and then presents corresponding solutions.The details are as follows:First,this thesis proposes a privacy protection method based on historical proximity location in the European space.It provides two solutions to address the protection of the privacy of the location in both instantaneous query and continuous query.The main idea of the method is that using the location of the user in the vicinity of the historical location in place of the user's current location to upload to the LBS server(SP).The method ensures that the user can get the location-based service while service providers can not get the location information of the user.Compared with other location privacy-preserving methods,this method improves query quality and querying efficiency.Second,the centralized structure is easily to be attacked by hackers and has poor performance for massive data request.This thesis proposes a privacy protection method based on independent structure.Users can get location services by interacting with the SP.First of all,users choose the initial query range at the mobile terminal.Then,they can interacts with the SP to refine the scope of the query and ultimately determine the real query scope.Third,the distribution of users on different road sections are uneven in the road network environment and it will give rise to the edge-weight attack.It proposes a privacy protection method based on historical proximity location in the road network environment.By using the historical proximity points,the weights of different edges in the road network are balanced.Besides,selecting the edges that are adjacent to the user's edge to form an implicit edge set to improve query efficiency and reduce query overhead.