Privacy and integrity preserving multi-dimensional range queries for cloud computing
Fei Chen, Alex X. Liu · 2014
In cloud computing, a cloud provider hosts the data of an organization and replies query results to the customers of the organization. Because organization's data are confidential and the cloud provider cannot be fully trusted, some schemes have been proposed to preserve data privacy and query result integrity. However, these schemes either include false positives in query results, or are too expensive. In this paper, we propose an effective and efficient privacy and integrity preserving scheme for multi-dimensional range queries. To preserve privacy, we propose an order-preserving hash-based function to encode both data and queries so that a cloud provider can correctly process encoded queries over encoded data without knowing their values. To preserve integrity, we propose a new data structure called local bit matrices that allows a customer to verify the integrity of a query result with a high probability. Experimental results show that our scheme can efficiently process a dataset with one million data items.