Secure and efficient range queries on outsourced databases using Rp-trees

We show how to execute range queries securely and efficiently on encrypted databases in the cloud. Current methods provide either security or efficiency, but not both. Many schemes even reveal the ordering of encrypted tuples, which, as we show, allows adversaries to estimate plaintext values accurately. We present the R̂-trees, a hierarchical encrypted index that may be securely placed in the cloud, and searched efficiently. It is based on a mechanism we design for encrypted halfspace range queries in ℝ d , using Asymmetric Scalar-product Preserving Encryption. Data owners can tune the R̂-trees parameters to achieve desired security-efficiency tradeoffs. We also present extensive experiments to evaluate R̂-trees performance. Our results show that R̂-trees queries are efficient on encrypted databases, and reveal far less information than competing methods.