Privacy Preserving kNN Spatial Query with Voronoi Neighbors

Abstract

With the increased demand for outsourcing databases, there is a demand to enable secure and efficient communications. The concern regarding outsourcing data is mainly providing confidentiality and integrity to the data. This paper proposes a novel solution to answering kNN queries at the cloud server over encrypted data. Data owners transform their data from a native domain to a new domain to assist in nearest neighbors’ classification. The transformation is achieved by Voronoi diagram, which transforms the data space into numerous small regions, simplifying the nearest neighbor search. However, because the regions that make up a Voronoi diagram are irregularly shaped, the search through the network becomes hard to accomplish.