Description

With the increasing popularity of cloud computing, huge amount of documents are outsourced to the cloud for reduced management cost and ease of access. Using cloud computing, individuals can store their data on remote servers and allow data access to public users through the cloud servers. At the outsourced data are likely to contain sensitive privacy information, they are typically encrypted before uploaded to the clod. This, however, significantly limits the usability of outsourced data due to the difficulty of searching over the encrypted data. In this paper, we address this issue by developing the fine-grained multi-keyword search schemes over encrypted clod data. Our original contributions are three-fold. First, we introduce the relevance source and preference factor upon keywords which enables the precise keyword search and personalized user experience. Second, we develop a practical and very efficient multi-keyword search scheme. The proposed scheme can support complicated logic search the mixed “AND”, “OR” and “NO” operations of keywords. Third we further employ the classified sub- dictionaries technique to achieve better efficiency on index building, trapdoor generating the query. Lastly, we analyze the security of the proposed schemes in terms of confidentiality of documents, privacy protection of index and trapdoor, and unlink ability of trapdoor. Through extensive experiments using the real-world dataset, we validate the performance of the proposed scheme can achieve the same security level comparing to the existing ones and better performance in terms of functionality, query complexity and efficiency.