Enabling efficient and verifiable multi-keyword ranked search over encrypted cloud data

With the prevalence of the cloud computing, data owners can outsource their data to the cloud server to enjoy convenient services. To ensure the user's data confidentiality, the outsourced data are usually stored in an encryption form on the cloud server, which makes it extremely difficult to search the specific encrypted documents matching some keywords from the cloud server for users. To address this issue, in this paper, we develop a multi-keyword ranked search scheme over encrypted cloud data, which also supports search results verification. To achieve efficient multi-keyword search, we construct a special data structure QSet based on an inverted index structure. To reduce the search complexity, we use the strategy that firstly searching the estimated least frequent keyword in the query to significantly narrow down the number of searching documents. Within this framework, to support ranked search, we utilize the common TF×IDF rule to compute the relevance scores of documents matching a given search request. To resist malicious behaviors of the cloud server, we generate a binary vector for each keyword and use MAC to check the authenticity of the returned ciphertexts. The security analysis demonstrates that our proposed schemes are semantic secure in the adaptive setting. Extensive experimental evaluation shows the efficiency in the computation overhead of search and verification.