User Privacy Protection For Location Based Service

In recent years, with the research of sensor technology and mobile devices, a variety of location-based services (LBS) came into being, and has been widely used in person life. At the same time of enjoying these services, the location of a user privacy issues have gradually become the focus of attention. So how to balance the relationship between service quality and privacy protection is the key to solve the problem. Currently,location privacy has become a hot research for experts and scholars.The purpose of this algorithm on location privacy research is to provide user service queries while protecting users’ privacy. In this paper, analyzes location privacy threats and gives a detailed introduction for existing location privacy protection progress. Therefore, on this basis, for LBS location privacy protection, we propose two kinds of complete program, with different models. Details are as follows:(1) In the first scheme, we proposes a distributed model with users’ cooperation and design the corresponding scheme. In this scheme, when constructing the anonymous area, we use Bayesian Nash Equilibrium and Secure Multiparty Sum technologies to ensure that the user information privacy; when processing the query results, we introduce the Voronoi method to increase the query efficiency. New scheme gives full consideration to the selfishness and unreliability of users. Hence it can not only provide the protection of user privacy, but also improve the performance of the services.(2) In the second scenario, we propose two models, divided into non-collusion attack and collusion attack. The models contain two database servers, the two data services respectively recorde according the abscissa and ordinate. The first method is relatively simple, direct inquiries from the two servers, respectively, and then take the intersection. The second method add the hardware-based PIR to resist the case of two servers conspiracy. And we have also considered sparse distribution of the point of interest (POI), in order to make better the storage of data,we add the index table to improve query efficiency. In the final analysis, it can be seen in terms of the efficiency or safety of the method is superior to the other.This papers have positive significance in regard to location privacy protection algorithm research.