Privacy preserving search scheme over encrypted data in cloud

Abstract

Due to the increasing quality of cloud computing, more and more information owners are actuated to source their information to cloud servers for nice convenience and reduced price in information management. However, sensitive information ought to be encrypted before outsourcing for privacy necessities, that obsoletes information utilization like keyword-based document retrieval. during this paper, we present a secure multi-keyword stratified search theme over encrypted cloud information, that at the same time supports dynamic update operations like deletion and insertion of documents. Specifically, the vector area model and therefore the widely-used TFIDF model are combined in the index construction and question generation. we construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithmic rule to produce economical multi-keyword stratified search. The secure kNN algorithmic rule is employed to cipher the index and question vectors, and in the meantime guarantee correct connection score calculation between encrypted index and question vectors. so as to resist statistical attacks, phantom terms are additional to the index vector for bright search results . owing to the utilization of our special tree-based index structure, the planned theme can do sub-linear search time and upset the deletion and insertion of documents flexibly. Extensive experiments are conducted to demonstrate the potency of the planned theme.