Multi-Keyword Ranked Search and Data Indexing in Secure Cloud Environment

Abstract

A Keyword Based Data Indexing and Receiving in Protected Cloud Environment due to the increasing popularity of cloud computing, more and more data owners are motivated to outsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval. In this paper, we have a tendency to gift a secure multi-keyword hierarchical search theme over encrypted cloud knowledge that at the same time supports dynamic update operations like deletion and insertion of documents. Specifically, the vector house model and, therefore, the widely-used tf×df model are combined within the index construction and question generation. We have a tendency to construct a special tree-based index structure and propose a “greedy depth-first search” algorithmic rule to supply economical multi-keyword hierarchical search. The secure knn algorithmic rule is employed to cypher the index and question vectors, and in the meantime guarantee correct connexion score calculation between encrypted index and question vectors. So, as to resist applied mathematics attacks, phantom terms are extra to the index vector for glaring search results.