Research On Location Privacy Protection Algorithm Based On Semantic Diversity

With the popularity of smart phones and the improvement of storage performance and computing performance,more and more people use LBS(Location-based service)to serve the social life.However,frequent access to the LBS server e xposes the user's personal location information,thereby revealing the user's personal privacy.As privacy becomes our growing concern today,how to solve this problem of location privacy leakage has become the focus of current research.In order to solve the problem of user location privacy,the commonly used method is location privacy protection algorithm based on dummy location.Since the accuracy of the request result is unstable and the semantic information contained in the anonymous region leads to the privacy of the user in this algorithm,two new location privacy preserving algorithms are proposed in this paper,which are the following two aspects:1.Based on the characteristics of high dummy location generation and easy generation on the client side,a new algorithm based on centroid for all dummy location privacy protection is proposed.The algorithm generates all dummy location on the client side and searches the nearest neighbor with the centroid method on the server side.The experimental results shows that,compared with the traditional method,our proposed method can not only protect the privacy of the user's location,but also reduce the communication cost,improve the accuracy of the return ed result of the server,and reduce the request processing time of the server side.2.A location privacy protection algorithm based on L-diversity is proposed.In this paper,we introduce the concept of semantic location SL(Sematic Location),and use the 24 dimension vector to mark the semantic location according to the user access time.We use the cosine theorem to distinguish different semantic positions,and use the semantic diversity of L as the standard of dummy location generation,that is,the semantic location information contained in the generated dummy location is not less than L.Experimental results show that the algorithm improves the location entropy,relative anonymity RAL and other experimental indexes greatly.Compared with the traditional method,the fake address generated by the algorithm can effectively prevent the attacker from carrying out semantic attacks.