Description

In mobile cloud computing, a fundamental application is to outsource the mobile data to external cloud servers for scalable data storage. The outsourced data, however, need to be encrypted due to the privacy and con_dentiality concerns of their owner. This results in the distinguished dif_culties on the accurate search over the encrypted mobile cloud data. To tackle this issue, in this paper, we develop the searchable encryption for multi-keyword ranked search over the storage data. Speci_cally, by considering the large number of outsourced documents (data) in the cloud, we utilize the relevance score and k-nearest neighbor techniques to develop an ef_cient multi-keyword search scheme that can return the ranked search results based on the accuracy. Within this framework, we leverage an ef_cient index to further improve the search ef_ciency, and adopt the blind storage system to conceal access pattern of the search user. Security analysis demonstrates that our scheme can achieve con_dentiality of documents and index, trapdoor privacy, trapdoor unlinkability, and concealing access pattern of the search user. Finally, using extensive simulations, we show that our proposal can achieve much improved ef_ciency in terms of search functionality and search time compared with the existing proposals.