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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.

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Index Terms

Computer Science
Information Sciences

Keywords

Privacy preservation Data publishing Data security Pattern Recognition Data Mining.