International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Science , Computer Science and Engineering

Volume5,March 2018,

Topic : Efficient Central Keyword Based Search Method over Encrypted Data in Cloud

Authors:A.Ramya || D.Udhaya chandrika, S.Sureka, R.Vinothini

Abstract:Keyword based search is a important aspect, when searching the data in cloud. Keywords may have a certain grammatical relationship among them which reflect the importance of keywords from the user’s perspective intuitively. Proposed system has relationship among query keywords into consideration and designs a keyword weighting algorithm to show the importance of distinction of the keywords. Key word weighting algorithm accurately and efficiently localizes the central keyword that the user is interested in. We can choose the central keyword (not all keywords) of the query to extend. When a user inputs some query keywords, our scheme can effectively and accurately locate and extend the semantics of the central keyword. The returned results should be relevant to both the multiple keywords that the user inputs and the extension keyword. To calculate the relevance scores between keywords and files, we use the widely used TF-IDF rule, where TF (term frequency) denotes the frequency of a given keyword in a document and IDF (inverse document frequency) represents the importance of a keyword. When the data owner updates the dataset, the TFIDF values are also changed. To enable updating, we make a few changes in the trapdoor and index generation by inserting the IDF values into the query vector and the TF values into the index vector, respectively.

Keywords: Trapdoor, TF-IDF rule, MRSE, weighting algorithm, central keyword

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DOI: 01.1617/vol5/iss3/pid02183

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Dr. Allon Guez
Professor, Drexel University,

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Thomson Reuters ID : q-6288-2016.
ORCiD Research ID : 0000-0001-9540-6799

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Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
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