Privacy Preserving Search Over Encrypted Data with Secure and Dynamic Operation in Cloud Computing - Patil, Poonam; Mane, Seema (International Journal of Computer Sciences and Engineering, 2020)
Due to the increasing significance of cloud computing, additional and tremendous information of data owners are made to outsource their information to cloud servers for excellent convenience and to lessen cost in information management. However, sensitive information ought to be encrypted before outsourcing for privacy needs that obsoletes information utilization like keyword-based document retrieval. In this paper, a secure multi-keyword search method over encrypted cloud data is described. At the same time it also supports dynamic update operations like deletion and insertion of documents. For index construction and query generation, the vector space model and widely-used TF_IDF model both are combined. A special tree- based index structure is constructed and a “Greedy Depth-first Search” method is proposed to produce economical multi-keyword ranked search. The secure KNN is used to encrypt the index and vectors. It also guarantees about correctness in appropriate score calculation between encrypted index and query vectors. In order to stop statistical attacks, phantom terms are intercalary to the index vector for accurate search results. As special tree-based index structure is used, the proposed method is able to do sub- linear search time and also handle the deletion and insertion of documents flexibly.