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An Ascent of Big Data on Cloud: A Study

by Gunjan Aggarwal, Deepti Sahu, Megha Chabbra
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 182 - Number 16
Year of Publication: 2018
Authors: Gunjan Aggarwal, Deepti Sahu, Megha Chabbra
10.5120/ijca2018917809

Gunjan Aggarwal, Deepti Sahu, Megha Chabbra . An Ascent of Big Data on Cloud: A Study. International Journal of Computer Applications. 182, 16 ( Sep 2018), 11-13. DOI=10.5120/ijca2018917809

@article{ 10.5120/ijca2018917809,
author = { Gunjan Aggarwal, Deepti Sahu, Megha Chabbra },
title = { An Ascent of Big Data on Cloud: A Study },
journal = { International Journal of Computer Applications },
issue_date = { Sep 2018 },
volume = { 182 },
number = { 16 },
month = { Sep },
year = { 2018 },
issn = { 0975-8887 },
pages = { 11-13 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume182/number16/29945-2018917809/ },
doi = { 10.5120/ijca2018917809 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:11:34.955962+05:30
%A Gunjan Aggarwal
%A Deepti Sahu
%A Megha Chabbra
%T An Ascent of Big Data on Cloud: A Study
%J International Journal of Computer Applications
%@ 0975-8887
%V 182
%N 16
%P 11-13
%D 2018
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Cloud computing is an intense innovation to perform massive scale and complex computing. It wipes out the need to keep up costly processing equipment, committed space and programming. Gigantic development in the size of information or big data generated through cloud computing has been observed. The term Big Data isn't just about the extent of information that comes in pet bytes or zeta bytes; rather it is more about capability to handle huge amounts of data. Tending to big data is a challenging and time requesting task for an expansive computational framework to guarantee productive data processing and analysis. The rise of big data in cloud computing and enhancing the security of big data is reviewed in this study.

References
  1. R.Devankuruchi “Analysis of Big Data Over the Years” International Journal of Scientific and Research Publications, Volume 4, Issue 1, January 2014 1 ISSN 2250-3153.
  2. Steve Sonaka “Big Data and the Ag sector: More than lots of numbers” International food and agribusiness review, volume 17 issue 1, 2014.
  3. A Katal, Wazid M, and Goudar R.H. "Big data: Issues, challenges, tools and Good practices.". Noida: 2013, pp. 404 – 409, 8-10 Aug. 2013.
  4. Ms.Manishasaini, Ms.PoojaTaneja, Ms.PinkiSethi “Big Data Analytics: Insights and Innovations” International Journal of Engineering Research and Development ,Volume 6, Issue 10 April 2013 e-ISSN: 2278-067X, p-ISSN: 2278-800X.
  5. S. Chaudhuri, “What Next?: A Half-Dozen Data Management Research Goals for Big Data and the Cloud,” Proc. 31st Symp. Principles of Database Systems (PODS ’12), pp. 1-4, 2012.
  6. D. Zissis and D. Lekkas, “Addressing Cloud Computing Security Issues,” Future Generation Computer Systems, vol. 28, no. 3, pp. 583- 592, 2011.
  7. H. Takabi, J.B.D. Joshi, and G. Ahn, “Security and Privacy Challenges in Cloud Computing Environments,” IEEE Security and Privacy, vol. 8, no. 6, pp. 24-31, Nov. 2010.
  8. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, “Workload-Aware Anonymization Techniques for Large-Scale Data Sets,” ACM Trans. Database Systems, vol. 33, no. 3, pp. 1-47, 2008.
  9. B.C.M. Fung, K. Wang, and P.S. Yu, “Anonymizing Classification Data for Privacy Preservation,” IEEE Trans. Knowledge and Data Eng., vol. 19, no. 5, pp. 711-725, May 2007.
  10. X. Xiao and Y. Tao, “Anatomy: Simple and Effective Privacy Preservation,” Proc. 32nd Int’l Conf. Very Large Data Bases (VLDB ’06), pp. 139-150, 2006.
  11. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, “Mondrian Multidimensional K-Anonymity,” Proc. 22nd Int’l Conf. Data Eng. (ICDE ’06), 2006.
  12. K. LeFevre, D.J. DeWitt, and R. Ramakrishnan, “Incognito: Efficient Full-Domain K-Anonymity,” Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’05), pp. 49-60, 2005.
  13. L. Sweeney. K-anonymity: A model for protecting privacy. Int. J. Uncertain. Fuzz., 10(5):557–570, 2002
Index Terms

Computer Science
Information Sciences

Keywords

Big Data Data Anonymization Cloud Computing

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