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

Monthly Journal for Science , Computer Science and Engineering

Volume4,June 2017,

Topic : A Secure Deduplication Mechanism for Sensitive Data in Public Cloud Storage

Authors:Deepa P.B || Dr.Rudramurthy M.S

Abstract:nowadays, cloud-based services are gaining more importance in leveraging services for large scale storage and distribution. These provide cost effectiveness, time saving and efficient utilization of computing resources. Many enterprises have decided to envision a staged migration for their data to public cloud, for better management of backup data. As data progressively grows, the cloud storage systems continuously face challenges in saving storage capacity. Data Deduplication gives solution to such challenges. It is a data compression technique for eliminating the redundant data. Assuming that cloud service provider may not be trustworthy (i.e. is honest but curious). The security, bandwidth and latency are of top concerns for an enterprise to store sensitive data in the public cloud storage. Considering these security challenges, we propose and implement a client side deduplication scheme for securely storing enterprise sensitive data via the pubic cloud. Efficiently and reliably managing the huge number of convergent keys by the user is a critical issue. Hence we have built a system where each convergent key is secured and the same is outsourced to the cloud. To avoid the weakness of convergent encryption, double encryption is done. By following this method, we can save storage space and cost. It also reduces bandwidth and ensures better confidentiality towards unauthorized users..

Keywords: Data deduplication, convergent encryption, and side channel attack

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DOI: 01.1617/vol4/iss6/pid69327

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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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