Effective Secure Multi-keyword Top-k Retrieval over Relational Databases

Keyword has emerging as a promising pattern for data outsourcing and high-quality data services. However, concerns of sensitive information on potentially cause privacy problems. Data encryption protects data security to some extent, but at the cost of compromised efficiency. Searchable symmetric encryption (SSE) allows retrieval of encrypted data. In this paper, we focus on addressing data privacy issues using SSE. For the first time, we formulate the privacy issue from the aspect of similarity relevance and scheme robustness. We observe that server-side ranking based on order-preserving encryption (OPE) inevitably leaks data privacy. To eliminate the leakage, we propose a two-round searchable encryption (TRSE) scheme that supports top-k multi keyword retrieval. In TRSE, we employ a vector space model and homomorphism encryption. The vector space model helps to provide sufficient search accuracy, and the homomorphism encryption enables users to involve in the ranking while the majority of computing work is done on the server side by operations only on cipher text. As a result, information leakage can be eliminated and data security is ensured. Thorough security and performance analysis show that the proposed scheme guarantees high security and practical efficiency. Keywords— patteren, sensitive, privacy, efficiency, encryption, keyword search, homomorphism, vector,