Paper Details

Due to the increasing popularity of cloud computing, more and more data owners are motivated tooutsource their data to cloud servers for great convenience and reduced cost in data management. However, sensitivedata should be encrypted before outsourcing for privacy requirements, which obsoletes data utilization like keywordbased document retrieval. In this paper, we present a secure multi-keyword ranked search scheme over encrypted clouddata, which simultaneously supports dynamic update operations like deletion and insertion of documents. Specifically,the vector space model and the widely-used TF_IDF 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 provideefficient multi-keyword ranked search. The secure kNN algorithm is utilized to encrypt the index and query vectors, andmeanwhile ensure accurate relevance score calculation between encrypted index and query vectors. In order to resiststatistical attacks, phantom terms are added to the index vector for blinding search results . Due to the use of our specialtree-based index structure, the proposed scheme can achieve sub-linear search time and deal with the deletion andinsertion of documents flexibly. Extensive experiments are conducted to demonstrate the efficiency of the proposedscheme.

Dr .Mohammed Abdul Waheed, Sandeep, “A Safe and Runtime Multi-Keyword Ranked Search for Encrypted Information over Cloud Data”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 8, pp. 93-99, August 2017.