A Deduplication Aware similarity in Cloud with Secure Deduplication of Encrypted Data

Authors

  • S. Palani  Asst. Professor Department of Computer Applications Sri Venkateswara College of Engineering and Technology(Autonomous) Chittoor, Andhra Pradesh, India
  • P. Bharath Kumar Reddy  PG scholar Department of Computer Applications Sri Venkateswara College of Engineering and Technology(Autonomous) Chittoor, Andhra Pradesh, India
  • K. Roja  PG scholar Department of Computer Applications Sri Venkateswara College of Engineering and Technology(Autonomous) Chittoor, Andhra Pradesh, India

Keywords:

Data deduplication, delta compression, resemblance Detection.

Abstract

Data reduction has become progressively necessary in storage systems owing to the explosive growth of digital data within the world that has ushered within the big data era. One in every of the most challenges facing large-scale data reduction is the way to maximally observe and eliminate redundancy at terribly low overheads. In this paper, we present a our scheme, a low-overhead Deduplication-Aware resemblance detection and Elimination theme that effectively exploits existing duplicate-adjacency data for extremely economical resemblance detection in data deduplication primarily based backup/archiving storage systems. the most plan behind our scheme is to use a theme, call Duplicate-Adjacency primarily based resemblance Detection (DupAdj), by considering any two data chunks to be similar (i.e., candidates for delta compression) if their various adjacent data chunks are duplicate in a very deduplication system, and then further enhance the resemblance detection efficiency by an improved super-feature approach.

References

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Published

2018-04-30

Issue

Section

Research Articles

How to Cite

[1]
S. Palani, P. Bharath Kumar Reddy, K. Roja, " A Deduplication Aware similarity in Cloud with Secure Deduplication of Encrypted Data , IInternational Journal of Scientific Research in Computer Science, Engineering and Information Technology(IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.403-408, March-April-2018.