Efficient Multikeyword Ranked Search over Encrypted Cloud Data with Rank Integrity

Due to the high popularity of cloud computing, more data owners are motivated to outsource the data to the cloud server. In that sensitive data will be encrypted before outsourcing to the cloud server for security purpose. In this paper, we introduce a secure multi-keyword ranked search over encrypted cloud data, which performs dynamic update operations like deletion and insertion of documents. By combining the vector space model and widely used TFxIDF model for the index construction and query generation. By constructing a special tree-based index structure and introduce “Greedy Depth First Search” algorithm that gives effective multi-keyword ranked search. Secure KNN algorithm is used to encrypt the index and query vectors, and also gives accurate relevance score calculation between encrypted index and query vectors. Due to the special tree-based index structure, it can achieve sub-linear search time and perform deletion and insertion of documents flexibly. Using multi-keyword ranked search over encrypted cloud data the files can be retrieved based on ranking. Thus, the ranking provides similar files from the cloud server it cannot assure that retrieved files are same or not. In this paper ranking is tested to the correctness of its order. The Rank test method is used to check the integrity of the rank order of the search results. Since the rank is fixed by the cloud server is tested and the user can get accurate results and so privacy can be improved.