CFP last date
20 June 2024
Reseach Article

A Review of Privacy Preservation Technique

by Avinash Kumar Singh, Narayan P. Keer, Anand Motwani
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 90 - Number 3
Year of Publication: 2014
Authors: Avinash Kumar Singh, Narayan P. Keer, Anand Motwani
10.5120/15554-4239

Avinash Kumar Singh, Narayan P. Keer, Anand Motwani . A Review of Privacy Preservation Technique. International Journal of Computer Applications. 90, 3 ( March 2014), 17-20. DOI=10.5120/15554-4239

@article{ 10.5120/15554-4239,
author = { Avinash Kumar Singh, Narayan P. Keer, Anand Motwani },
title = { A Review of Privacy Preservation Technique },
journal = { International Journal of Computer Applications },
issue_date = { March 2014 },
volume = { 90 },
number = { 3 },
month = { March },
year = { 2014 },
issn = { 0975-8887 },
pages = { 17-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume90/number3/15554-4239/ },
doi = { 10.5120/15554-4239 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:10:07.380839+05:30
%A Avinash Kumar Singh
%A Narayan P. Keer
%A Anand Motwani
%T A Review of Privacy Preservation Technique
%J International Journal of Computer Applications
%@ 0975-8887
%V 90
%N 3
%P 17-20
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Privacy-preserving is one of the most important challenges in a computer world, because of the huge amount of sensitive information on the internet. The paper contains several privacy preservation techniques for data publishing in the real world. There are several privacy attacks are associate but among of them mainly two attacks are record linkage and attribute linkage. Many scientists have proposed methods to preserve the privacy of data publishing such as K-anonymity, ?-diversity, t-closeness. K-anonymity can prevent the record linkage but unable to protect attribute linkage. ?-diversity technique overcomes the drawback of k-anonymity technique but it fail to protect from membership discloser attack. T-closeness technique prevents to attribute discloser attack but it fail in identity disclosure attack. Its computational complexity is large. In this paper we present the novel technique call slicing which to be implemented with various data set through prevent the privacy preservation for data publishing. The goals of this paper is re-analysis a number of privacy preservation of data mining technique clearly and then study the advantages and disadvantages of this technique.

References
  1. R. Mahesh, T. Meyyappan, "Anonymization Technique through Record Elimination to Preserve Privacy of Published Data", Proceedings of the 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, February 21-22. Ding, W. and Marchionini, G. 1997 A Study on Video Browsing Strategies. Technical Report. University of Maryland at College Park.
  2. Tiancheng Li, Ninghui Li, Senior Member, IEEE, Jia Zhang, Member, IEEE, and Ian Molloy "Slicing: A New Approach for Privacy Preserving Data Publishing" Proc. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 24, NO. 3, MARCH 2012.
  3. Neha v. Moghre, Sulbha patil, "Slicing: An approach for privacy preservation in high dimensional data using anonymization technique" Proceedings of Fifth IRAJ International Conference, 15th September 2013, Pune, India, ISBN: 978-93-82702-29-0.
  4. Benjamin C. Fung, K E wang, Rui Chen, Philip S Yu "Privacy-Preserving Data Publishing: A Survey of Recent Developments" ACM Computing Surveys, Vol. 42, No. 4, Article 14, Publication date: June 2010.
  5. Ninghui Li, Tiancheng Li, Suresh Vengakatasubramaniam, "t-Closeness: Privacy Beyond k-Anonymity and ?-Diversity", International Conference on Data Engineering, 2007, pp106-115.
  6. A. Machanavajjhala, J. Gehrke, D. Kifer, and M. Venkitasubramaniam, "?-diversity: Privacy beyond k-anonymity", In Proc. 22nd Intel international Conference on data engineering. (ICDE), 2006, pp24. Y. T. Yu, M. F. Lau, "A comparison of MC/DC, MUMCUT and several other coverage criteria for logical decisions", Journal of Systems and Software, 2005, in press.
  7. M. Alphonsa1, V. Anandam2, D. Baswaraj3" Methodology of Privacy Preserving Data Publishing by Data Slicing" International Journal of Computer Science and Mobile Applications, Vol. 1 Issue. 3, September- 2013, pg. 30-34.
  8. D. Mohanapriya, Dr. T. Meyyappan "High Dimensional Data Handling Technique Using Overlapping Slicing Method for Privacy Preservation" International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 6, June 2013.
  9. Amar Paul Singh, Ms. Dhanshri Parihar "A Review of Privacy Preserving Data Publishing Technique" International Journal of Emerging Research in Management &Technology ISSN: 2278-9359 (Volume-2, Issue-6) June 2013.
  10. Neha V. Mogre, Prof. Girish Agarwal, Prof. Pragati Patil "Privacy Preserving for High-dimensional Data using Anonymization Technique" International Journal of Advanced Research in Computer Science and Software Engineering Volume 3, Issue 6, June 2013 ISSN: 2277 128X.
  11. Neha V. Mogre, Prof. Girish Agarwal, Prof. Pragati Patil" A Review On Data Anonymization Technique For Data Publishing" International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 10, December- 2012 ISSN: 2278-0181.
  12. Bin Zhou, Jian Pei, WoShun Luk "A Brief Survey on Anonymization Techniques for Privacy Preserving Publishing of Social Network Data" August 20, 2007.
  13. Bee-Chung Chen, Daniel Kifer, Kristen LeFevre and Ashwin Machanavajjhala "Privacy-Preserving Data Publishing" Vol. 2, Nos. 1–2 (2009) 1–167.
  14. L. Sweeney, "k-anonymity: A model for protecting privacy," International Journal on Uncertainty, Fuzziness and Knowledge-based Systems, vol. 10, no. 5, pp. 557–570, 2002.
  15. Neha Jamdar, Vanita Babane "Survey on Privacy-Preservation in Data Mining Using Slicing Strategy" Volume 2 Issue 11, November 2013.
  16. Pingshui Wang, Jiandong Wang, Xinfeng Zhu ,Jian Jiang "Research on Privacy Preserving Data Mining" 2012 International Conference on Biological and Biomedical Sciences Advances in Biomedical Engineering, Vol. 9.
Index Terms

Computer Science
Information Sciences

Keywords

Privacy preservation Data publishing Data security Pattern Recognition Data Mining.