An efficient algorithm for privacy in nearest Neighbourhood search in MQMO for point clouds
Phaltane Anjali D, Vidya Jagtap
Due to the growth in mobile phones, the location based service (LBS) market is growing tremendously fast. Many mobile phone applications uses LBS such as store finder, car navigation system etc. LBS provide services to mobile users based on location & data profile of user’s hence users private information may get violated. In order to protect users private information many solutions are offered but most of them only addressed on snapshot query and no support for continual query and Moving Query Moving Object (MQMO). This paper focuses on MQMO & also protects users’ private information using PIR. In this paper we proposed a system to reduce the communication cost in client-server architecture as an object needs to report its location to the server only when it leaves its safe region or server sends location update request. Hilbert transform is used to find shortest path to reach destination & protection of user data. Voronoi diagram is used for space partitioning and cell binding. Also we describe a motion adaptive indexing scheme for indexing the database of moving continuous query. The concept of motion sensitive bounding boxes (MSBs) is used in order to model moving objects & moving queries.
Phaltane Anjali D, Vidya Jagtap. An efficient algorithm for privacy in nearest Neighbourhood search in MQMO for point clouds. International Journal of Academic Research and Development, Volume 3, Issue 2S, 2018, Pages 31-36