Multi-keyword ranked search supporting synonym query over encrypted data in cloud computing

Abstract

Cloud computing becomes increasingly popular. To protect data privacy, sensitive data should be encrypted by the data owner before outsourcing, which makes the traditional and efficient plaintext keyword search technique useless. The existing searchable encryption schemes support only exact or fuzzy keyword search, not support semantics-based multi-keyword ranked search. In the real search scenario, it is quite common that cloud customers' searching input might be the synonyms of the predefined keywords, not the exact or fuzzy matching keywords due to the possible synonym substitution (reproduction of information content) and/or her lack of exact knowledge about the data. Therefore, synonym-based multi-keyword ranked search over encrypted cloud data remains a very challenging problem. In this paper, for the first time, we propose an effective approach to solve the problem of synonym-based multi-keyword ranked search over encrypted cloud data. We make contributions mainly in two aspects: synonym-based search for supporting synonym query and multi-keyword ranked search for achieving more accurate search result. Two secure schemes are proposed to meet privacy requirements in two threat models of known ciphertext model and known background model. In enhanced scheme, the sensitive frequency information can be well protected by introducing some dummy keywords, which is not adopted in basic scheme. We give security analysis to justify the correctness and privacy-preserving guarantee of the proposed schemes. Extensive experiments on real-world dataset validate our analysis and show that our proposed solution is very efficient and effective in supporting synonym-based searching.