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Reseach Article

K-anonymity Model for Multiple Sensitive Attributes

Published on February 2012 by Nidhi Maheshwarkar, Kshitij Pathak, Narendra S. Choudhari
Optimization and On-chip Communication
Foundation of Computer Science USA
OOC - Number 1
February 2012
Authors: Nidhi Maheshwarkar, Kshitij Pathak, Narendra S. Choudhari
4ee85388-7e27-4c9f-97a8-021c2a5510a0

Nidhi Maheshwarkar, Kshitij Pathak, Narendra S. Choudhari . K-anonymity Model for Multiple Sensitive Attributes. Optimization and On-chip Communication. OOC, 1 (February 2012), 51-56.

@article{
author = { Nidhi Maheshwarkar, Kshitij Pathak, Narendra S. Choudhari },
title = { K-anonymity Model for Multiple Sensitive Attributes },
journal = { Optimization and On-chip Communication },
issue_date = { February 2012 },
volume = { OOC },
number = { 1 },
month = { February },
year = { 2012 },
issn = 0975-8887,
pages = { 51-56 },
numpages = 6,
url = { /specialissues/ooc/number1/5472-1010/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Optimization and On-chip Communication
%A Nidhi Maheshwarkar
%A Kshitij Pathak
%A Narendra S. Choudhari
%T K-anonymity Model for Multiple Sensitive Attributes
%J Optimization and On-chip Communication
%@ 0975-8887
%V OOC
%N 1
%P 51-56
%D 2012
%I International Journal of Computer Applications
Abstract

In today’s era acquiring information about others is not difficult task but securing this data form interlopers is a big deal. K-anonymity model used to protect released data. Released data which is available for public used may contain sensitive and non-sensitive data. But K-anonymity model faces changes when set of sensitive attributes are present in the data set. To achieve K-anonymous table with diversity may causes distortion of data in some extent. This paper proposed a new concept to minimize this data distortion without using tuple suppression for M-SA K-anonymity Model.

References
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Index Terms

Computer Science
Information Sciences

Keywords

K-anonymity Attacks on anonymous table l-diversity multiple sensitive attributes