A Survey on Dynamic multi keyword Ranked search scheme over Encrypted Cloud Data

Abstract

 Due to the developing popularity of cloud computing, increasingly facts owners are influenced to outsource their information to cloud servers for fantastic comfort and decreased price in facts management. However, touchy facts must be encrypted earlier than outsourcing for privateness requirements, which obsoletes data usage like key-word-based file retrieval. In this paper, we present a comfortable multi-key-word ranked seek scheme over encrypted cloud facts, which simultaneously supports dynamic update operations like deletion and insertion of documents. Mainly, the vector area model and the widely-used TF_IDF model are shared inside the index production and query era. We assemble a unique tree-based totally index shape and advocate a “greedy intensity-first search” algorithm to offer efficient multi-key-word ranked seek. The secure kNN algorithm is utilized to encrypt the index and query vectors, and in the meantime make sure correct relevance rating calculation among encrypted index and question vectors. As a way to defy statistical attacks, phantom terms are introduced to the index vector for blinding seek outcomes. Because of using our unique tree-based index structure, the proposed scheme can attain sub-linear search time and deal with the deletion and insertion of files flexibly. Massive experiments are carried out to demonstrate the efficiency of the proposed scheme.