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

Monthly Journal for Science , Computer Science and Engineering

Volume4,August 2017,

Topic : “Implementation of file level and block level deduplication and detecting attacks in cloud environment.”

Authors:Prof. Samita Mokal || Prof. Nilima Nikam, Prof. Vaishali Londhe

Abstract:In cloud computing, security and storage space management techniques are most important factors for improving the performance of cloud computing. Secure deduplication is a technique for eliminating duplicate copies of storage data, and provides security to them. To reduce storage space and upload bandwidth in cloud storage deduplication has been a well-known technique.. The basic idea in this paper is that we can eliminate duplicate copies of storage data and limit the damage of stolen data if we decrease the value of that stolen information to the attacker. This paper makes the first attempt to formally address the problem of achieving efficient and reliable key management in secure deduplication. we propose Sekey, User Behavior Profiling and Decoys technology. Sekey new construction in which users do not need to manage any keys on their own but instead securely distribute the convergent key shares across multiple servers for insider attacker. As a proof of concept, we implement Sekey using the Ramp secret sharing scheme and demonstrate that Sekey incurs limited overhead in realistic environments. User profiling and decoys, then, serve two purposes. First one is validating whether data access is authorized when abnormal information access is detected, and second one is that confusing the attacker with bogus information. We posit that the combination of these security features will provide unprecedented levels of security for the deduplication in insider and outsider attacker...

Keywords: Deduplication , proof of ownership, convergent encryption, key management, decoy technology.

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DOI: 01.1617/vol4/iss8/pid68257


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Editor-in-Chief

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Dr. Allon Guez
Professor, Drexel University,
USA


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IMPACT FACTOR: 4.890

ISSN(Online):2394-2320

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

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ACCEPTANCE RATIO

ACCEPTANCE RATIO: 28.69%
ARTICLES PUBLISHED:0521
PAPER RECEIVED:01730
Journal Code : IJERCSE
Electronic ISSN : 2394-2320
Impact Factor : 4.890
Frequency : monthly
Contact : info@ijercse.com


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