A k-Anonymous Location Privacy Protection Method of Polygon Based on Density Distribution

Abstract

In order to solve the problem of out-off-balance caused by accuracy of location information between privacy protection security and query service quality, considering basic information comprehensively such as the environment and geographical features and so on, and adopting k- anonymous privacy protection mechanism, we present a k-anonymous location privacy protection method of polygon based on density distribution. Firstly, a k-anonymous irregular polygon region is structured in whole area. Then, according to the preset anonymous region and density threshold, the better effects of anonymous are obtained by expanding the region or adding the random dummy locations. Experimental results show that the proposed method improves the efficiency of anonymous and query accuracy. The balance between privacy protection security and query quality is achieved.