Contact Project Developer Ashish D. Tiwari [astiwz@gmail.com]
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Cloud C#.NET ASP.NET BE-Engineering(CO/IT) ME-Engineering(CO/IT) BCS MCS BCA MCA MCM BSC Computer/IT MSC Computer/IT BE E&TC / ECE Diploma (CO/IT) IEEE-2015

A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data

Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data
Abstract-Synopsis-Documentation

Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data

Abstract


A Secure and Dynamic Multi-keyword Ranked Search Scheme over Encrypted Cloud Data 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 present a secure multi-keyword ranked search scheme over encrypted cloud data, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically, the vector space model and the widely-used TFIDF model are combined in the index construction and query generation. We construct a special tree-based index structure and propose a “Greedy Depth-first Search” algorithm to provide efficient multi-keyword ranked search. The secure kNN algorithm is utilized to encrypt the index and query vectors, and meanwhile ensure accurate relevance score calculation between encrypted index and query vectors. In order to resist statistical attacks, phantom terms are added to the index vector for blinding search results . Due to the use of our special tree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion and insertion of documents flexibly. Extensive experiments are conducted to demonstrate the efficiency of the proposed scheme.


EXISTING SYSTEM

The existing techniques on keyword-based information retrieval, which are widely used on the plaintext data, cannot be directly applied on the encrypted data. Downloading all the data from the cloud and decrypt locally is obviously impractical. All these multi keyword search schemes retrieve search results based on the existence of keywords, which cannot provide acceptable result ranking functionality. However, sensitive data should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keyword-based document retrieval.


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