Research On Location Privacy Protection Algorithm Based On Semantic Context

With the development of spatial location technology such as GPS,WiFi and the widespread use of mobile device,LBS(Location-Based Services)has been more and more popular in our daily life.As users need to provide their precise locations to the service providers to receive corresponding service,it's easy for the attackers to get user's real location.Then users' personal privacy as life style and hobbies may be speculated,even they will be tracked or attacked by the evildoers.Therefore,it's a serious problem to protect users' location privacy.This paper introduces and analyzes the advantages,disadvantages and scope of the existing location privacy system models and privacy approaches.Most of the existing approaches don't take semantic context into consideration,thus they are vulnerable to the attack based on semantic information.Introduce the progress of privacy protection technologies which have considered semantic context and point out that they have low service quality,then this paper proposes two personalized semantic location privacy preserving algorithms based on query optimization,namely the sensitive ratio based algorithm and incremental search algorithm.These two algorithms both start from user's location,then add neighbor locations until all locations form a location set which satisfies the privacy requirement.Take sensitive ratio as the choosing condition,the sensitive ratio based algorithm is local optimal.It brings down the query cost by selecting an optimal location every time.Incremental search algorithm combines global optimization and local optimization to reduce query cost.Global optimization means the algorithm will consider all possible neighbor locations and local optimization means only part of the considered locations will be selected for next selection.This paper uses NGMO simulation platform to execute experiments by comparing the proposed algorithms with the existing algorithms.The result shows that the anonymous success rate is higher than existing algorithm while the query cost is lower.