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

Monthly Journal for Science , Computer Science and Engineering

Volume5,April 2018,

Topic : An Efficient and Fine-grained Big Data Access Control Scheme with Privacy preserving Policy

Authors:M. Leela Amani || PK. VenkateswarLal, M. Sujatha, D. samatha, G. Subhasri

Abstract:How to manage the access of the massive amount of huge knowledge becomes a awfully difficult issue, particularly once huge knowledge ar keep within thecloud. Ciphertext-Policy Attribute based Encryption (CP-ABE) may be a promising secret writing technique that {allows} end-users to encode their knowledge beneath the access policies outlined over some attributes {of knowledge |of knowledge| of information} shoppers and solely allows data shoppers whose attributes satisfy the access policies to decode the information. In CP-ABE, the access policy is connected to the ciphertext in plaintext type, which can also leak some non-public data regarding end-users. Existing ways solely part hide the attribute values within the access policies, whereas the attribute names ar still unprotected. During this paper, we have a tendency to propose AN economical and fine-grained huge knowledge access management theme with privacy-preserving policy. Specifically, we have a tendency to hide the complete attribute (rather than solely its values) within the access policies. to help knowledge coding, we have a tendency to additionally style a unique Attribute Bloom Filter to judge whether or not AN attribute is within the access policy and find the precise position within the access policy if it's within the accesspolicy. Security analysis and performance analysis show thatour theme will preserve the privacy from any LSSS accesspolicy while not using a lot of overhead..

Keywords: Big Data; Access Control; Privacy-preserving Policy; Attribute Bloom Filter; LSSS Access Structure

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DOI: 01.1617/vol5/iss4/pid91620

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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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