Privacy-Aware Multi-Keyword Top-k Search over Untrust Data Cloud

Abstract

In this paper, we focus on data privacy of searchable symmetric encryption (SSE) in cloud computing. For the first time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness and then prove server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. In order to solve this problem, we propose a two round searchable encryption (TRSE) scheme, supporting top-k multi-keyword search, in which novel technologies, i.e., homomorphic encryption and vector space model, are employed. Vector space model helps to provide sufficient search accuracy, and homomorphic encryption enables users involve in the ranking while majority of computing work is still done on server-side by operations only on ciphertext. In this way, information leakage can be eliminated and data security is ensured. Thorough security analysis and performance analysis show that the proposed scheme guarantees high security and practical efficiency.