Location Privacy Protection Model Based On Semi-trusted Users

With the increasing maturity of wireless communication technology and the popularization of intelligent terminals,location-based service applications(LBS)have been fully developed.When users are asking for location service,they need to provide LBS service with user's own request content and location information.In the process,user's privacy is at risk of disclosure.The privacy protection based on location service has become a hot topic for scholars.The defects of current mainstream location privacy protection models are as follows: P2 P model faces the distrust between users,long response time and inaccurate feedback results and the trusted third-party server model faces heavy computing storage and some security risks.Aiming at a series of problems existing in the above mainstream models,this paper designs a new location privacy protection model based on the user's personalized choice of privacy protection level,combined with the P2 P structure and the TTP structure.The main research work of this thesis is as follows:(1)Design of N-personalized anonymous algorithm in Point-to-Point distributed structure.In the P2 P model,the N-personalized anonymity algorithm designed in this thesis can quickly find the cooperative users within the effective range and establish the anonymous area set by the user personalization.In addition,the algorithm can ensure that the communication between cooperative users does not expose their location information and identity information.Even if there are some untrusted users,it can also ensure the privacy security of each cooperative user.(2)Design of G-generalized region anonymous algorithm in Trusted Third-Party server.In the TTP model,according to the user's personalized privacy protection level,Geohash code the user's location information and determine the size of the anonymous area.In addition,Memcache is added to the TTP model to improve the query efficiency of users.(3)Experimental design and analysis.Experimental data show that both the Npersonalized anonymous algorithm and the G-generalized region anonymous algorithm perform better than traditional models.The T-P hybrid model structure has faster query speed and better system performance,especially when the parameters of privacy protection level become larger,the T-P hybrid model structure has better performance results.