A study of location privacy protection about kinteresting points query based on double anchors

With the continuous development of mobile internet, location-based services are widely used in our daily life. The issue of mobile user privacy disclosure is unavoidable. Attackers can acquire sensitive information such as user identity, privacy and so on, according to the user's location information. To solve the issue, this paper proposed an improved third-party anonymous server framework to protect the mobile user location for KNN (K-nearest neighbor) query. The framework prevents a third-party anonymous server from being attacked and thus compromise of user information. Meanwhile, it allocates part of the computation to mobile devices in order to reduce the possibility of computing performance constraints from the servers. On this basis, a new client POI (point of interest) search algorithm DATwist is put forward, which searches the POIs based on double anchors points. The DATwist algorithm can fix the defects that the POIs are distributed around the anchor points and the search results are unbalanced in the SpaceTwist algorithm, enabling a more accurate and effective KNN progress. Finally, the comparing experiments proved that the DATwist algorithm has more advantages than the HINN (homogeneous incremental nearest neighbor) algorithm in effectiveness and communication overhead with uniform distribution of POIs query results.