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Cloud Computing Security Mechanism Analysis: Encryption and Compression to enhance Security and save Cost in Cloud- A study

by Sajan Dung, Sandeep Sharma
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 164 - Number 9
Year of Publication: 2017
Authors: Sajan Dung, Sandeep Sharma
10.5120/ijca2017913701

Sajan Dung, Sandeep Sharma . Cloud Computing Security Mechanism Analysis: Encryption and Compression to enhance Security and save Cost in Cloud- A study. International Journal of Computer Applications. 164, 9 ( Apr 2017), 6-11. DOI=10.5120/ijca2017913701

@article{ 10.5120/ijca2017913701,
author = { Sajan Dung, Sandeep Sharma },
title = { Cloud Computing Security Mechanism Analysis: Encryption and Compression to enhance Security and save Cost in Cloud- A study },
journal = { International Journal of Computer Applications },
issue_date = { Apr 2017 },
volume = { 164 },
number = { 9 },
month = { Apr },
year = { 2017 },
issn = { 0975-8887 },
pages = { 6-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume164/number9/27509-2017913701/ },
doi = { 10.5120/ijca2017913701 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:10:50.501938+05:30
%A Sajan Dung
%A Sandeep Sharma
%T Cloud Computing Security Mechanism Analysis: Encryption and Compression to enhance Security and save Cost in Cloud- A study
%J International Journal of Computer Applications
%@ 0975-8887
%V 164
%N 9
%P 6-11
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Transfer of data from source to destination is of prime concern in case of advanced computing. Virtual machines in terms of nodes exist in advance computing. Users of advance computing could be fair or malicious in nature. In case of malicious nodes some defence mechanism is needed. This defence mechanism is provided in terms of encryption. In advance computing, cost is encounter on the basis of pay per use. So, security along with space conservation is issues to tackle in case of advance computing. Both of these issues are tackled by the use of data deduplication. Propose literature is concerned with analysing techniques which are used in existing literature to provide data deduplication for security and compression. The comparative analysis is provided to give worth of the study.

References
  1. A. Celesti, F. Tusa, M. Villari, and A. Puliafito, “An Approach to Enable Cloud Service Providers to Arrange IaaS , PaaS , and SaaS Using External Virtualization Infrastructures,” 2011.
  2. S. Lee, J. H. Song, and I. K. Kim, “CDA Generation and Integration for Health Information Exchange Based on Cloud Computing System,” vol. 1374, no. c, 2014.
  3. R. Buyya, “Introduction to the IEEE Transactions on Cloud Computing,” vol. 1, no. 1, pp. 3–21, 2013.
  4. K. Bousselmi, “Energy efficient partitioning and scheduling approach for Scientific Workflows in the Cloud,” 2016.
  5. U. Wajid, C. Cappiello, P. Plebani, B. Pernici, N. Mehandjiev, M. Vitali, M. Gienger, K. Kavoussanakis, D. Margery, D. G. Perez, and P. Sampaio, “On Achieving Energy Efficiency and Reducing CO 2 Footprint in Cloud Computing,” vol. 7161, no. c, 2015.
  6. I. Transactions, O. N. Circuits, S. For, and V. Technology, “Introduction to the Special Section on Visual Computing in the Cloud : Cloud Gaming and Virtualization,” vol. 25, no. 12, pp. 1955–1959, 2015.
  7. A. On and Y. For, “Introduction to the Special Section on Visual Computing in the Cloud : Fundamentals and Applications,” vol. 25, no. 12, pp. 1885–1887, 2015.
  8. J. H. Abawajy, S. Member, and A. Kelarev, “Large Iterative Multitier Ensemble Classifiers for Security of Big Data,” vol. 2, no. 3, 2014.
  9. X. Ding, J. Shan, and S. Jiang, “A General Approach to Scalable Buffer Pool Management,” vol. 9219, no. c, 2015.
  10. N. Kaurav, “An Investigation on Data De-duplication Methods And it ’ s Recent Advancements De-duplication De-Duplication Types,” 2014.
  11. D. T. Meyer and W. J. Bolosky, “A Study of Practical Deduplication.”
  12. Q. He, Z. Li, and X. Zhang, “Data Deduplication Techniques,” pp. 430–433, 2010.
  13. T. Y. J. Nagamalleswari, “Deduplication Techniques : A Technical Survey,” vol. 1, no. 7, pp. 318–325, 2014.
  14. A. Info, “PERFORMANCE COMPARISON OF DEDUPLICATION TECHNIQUES FOR STORAGE IN,” vol. 5, pp. 42–45, 2014.
  15. “A D VA N C E D D ATA D E D U P L I C AT I O N T E C H N I Q U E S A N D T H E I R,” 2013.
  16. J. Li, Y. K. Li, X. Chen, P. P. C. Lee, and W. Lou, “A Hybrid Cloud Approach for Secure Authorized Deduplication,” pp. 1–12, 2014.
  17. G. Sethi, S. Shaw, K. Vinutha, and C. Chakravorty, “Data Compression Techniques,” vol. 5, no. 4, pp. 5584–5586, 2014.
  18. D. Laney, S. Langer, C. Weber, P. Lindstrom, and A. Wegener, “Assessing the effects of data compression in simulations using physically motivated metrics 1,” vol. 22, pp. 141–155, 2014.
Index Terms

Computer Science
Information Sciences

Keywords

chunk based deduplication data deduplication data reduction redundant data.

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