Improved Multi-Keyword Ranked Search Mechanism over Encrypted Cloud Data
- Country : India
- Subject : Computer Science
Because of the expanding prominence of CLOUD computing, an ever-increasing number of information proprietors are inspired for outsourcing their information to the servers of cloud for extraordinary convenience as well as lessened price in management of Data. However, encryption of the delicate data must be done before outsourcing it for the security necessities, which obsoletes utilization of data like retrieving the documents based on the keyword. In this paper, we present a protected multi-keyword ranked search algorithm over the data stored on the CLOUD server in the encoded form, where operations which are dynamic are supported by it simultaneously like deletion and insertion of any document. For constructing an index and generating the query, the vector space model and the broadly used TF-IDF model are combined. Further, a tree based index structure has been constructed and to give a productive “multi-keyword” ranked search, we proposed a “Greedy Depth-first Search” algorithm. To encode a query vector and an index, we used a secure kNN algorithm as well as the accurate relevance score calculation between query vectors and an index is ensured. With a specific end goal to resist statistics attacks, phantom terms are added to the vector of indices for blinding items in the query. Sub-linear search time can be achieved by the proposed algorithm as well as insertion and deletion are managed to ensure the flexibility.