TRQED: Secure and Fast Tree-Based Private Range Queries over Encrypted Cloud

Abstract

With the prevalence of cloud computing, data owners are motivated to outsource their databases to the cloud. However, sensitive information has to be encrypted to preserve the privacy, which inevitably makes effective data utilization a challenging task. Existing work either focuses on keyword searches, or suffers from inadequate security guarantees or inefficiency. In this paper, we focus on the problem of multi-dimensional range queries over dynamic encrypted cloud data. We propose a Tree-based private Range Query scheme over dynamic Encrypted cloud Data (TRQED), which enables faster-than-linear range queries and supports data dynamics while preserving the query privacy and single-dimensional privacy simultaneously. TRQED achieves provable security against semi-honest adversaries under known background model. Extensive experiments on real-world datasets show that the overhead of TRQED is desirable, and TRQED is more efficient compared with existing work.