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An enhanced secure content de-duplication identification and prevention (ESCDIP) algorithm in cloud environment

  • J. K. PeriasamyEmail author
  • B. Latha
Review Article
  • 14 Downloads

Abstract

In cloud computing, de-duplication plays an essential role in detecting the de-duplication of encoded data with minimal computation and cost. De-duplication cleans the cloud datacentre’s unwanted storage and helps to identify the right owner of the content in the cloud. Even if there is only one copy of each data file stored in the cloud, the cloud has huge quantity of cloud users who own such data file. The existing method discussed a convergent encryption technique to solve the de-duplication problem. It also developed a system which does not allow storing any duplicate data in the cloud. However, the method does not assure consistency, reliability and confidentiality in cloud. Similar or different cloud users could store duplicated file in the cloud server, where cloud storage utilises high volume of storage. To find a solution for the above problems, the paper introduces enhanced secure content de-duplication identification and prevention (ESCDIP) algorithm to enhance the file-level and content-level de-duplication detection of encoded data with reliability in cloud environment. Every cloud user’s files contain an independent master key for encryption using ESCDIP technique and outsourcing them into the cloud. It reduces the overheads that are associated with the interactive duplication detection and query processes. The proposed method identifies the unique data chunking to store in the cloud. Based on experimental result, the ESCDIP method reduces 2.3 data uploading time in seconds, 2.31 data downloading time in seconds and 32.66% communication cost compared to existing approaches.

Keywords

Enhanced secure content de-duplication identification and prevention (ESCDIP) Cloud storage Data de-duplication Privacy preserving Data uploading time Data downloading time 

Notes

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Copyright information

© Springer-Verlag London Ltd., part of Springer Nature 2019

Authors and Affiliations

  1. 1.Faculty of Information and Communication EngineeringAnna UniversityChennaiIndia
  2. 2.Department of Computer Science and EngineeringSri Sairam Engineering CollegeChennaiIndia

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