Efficient outsourcing of secure k-nearest neighbour query over encrypted database

Abstract

Cloud computing allows a cloud user to outsource her data and the related computation to a cloud service provider to save storage and computational cost. This convenient service has brought a shift from the traditional client–server model to DataBase as a Service (DBaaS). Although DBaaS relieves the clients from the data management burdens, a significant concern about the data privacy remains. In this work, we focus on outsourcing secure k-nearest neighbour (k-NN) query, and provide the first sublinear solution (with preprocessing) with computational complexity O(klgn(lg2n+lg3k)). Our construction uses the data structure called kd-tree to achieve the sublinear query complexity. In order to protect data access patterns, garbled circuits are used to simulate Oblivious RAM (ORAM) for accessing data in the kd-tree. Compared with the existing solutions, our scheme imposes only constant overhead on both the data owner and the querying client.