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Reseach Article

A Comprehensive Study of Privacy Preservation Techniques in a Distributed Association Rule Mining

by Nusrat Jabeen. T, M.chidambaram
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 108 - Number 2
Year of Publication: 2014
Authors: Nusrat Jabeen. T, M.chidambaram

Nusrat Jabeen. T, M.chidambaram . A Comprehensive Study of Privacy Preservation Techniques in a Distributed Association Rule Mining. International Journal of Computer Applications. 108, 2 ( December 2014), 26-28. DOI=10.5120/18884-0163

@article{ 10.5120/18884-0163,
author = { Nusrat Jabeen. T, M.chidambaram },
title = { A Comprehensive Study of Privacy Preservation Techniques in a Distributed Association Rule Mining },
journal = { International Journal of Computer Applications },
issue_date = { December 2014 },
volume = { 108 },
number = { 2 },
month = { December },
year = { 2014 },
issn = { 0975-8887 },
pages = { 26-28 },
numpages = {9},
url = { },
doi = { 10.5120/18884-0163 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T22:41:57.812818+05:30
%A Nusrat Jabeen. T
%A M.chidambaram
%T A Comprehensive Study of Privacy Preservation Techniques in a Distributed Association Rule Mining
%J International Journal of Computer Applications
%@ 0975-8887
%V 108
%N 2
%P 26-28
%D 2014
%I Foundation of Computer Science (FCS), NY, USA

Association rule mining is a popular technique in data mining process which tries to find interesting associations and correlations among various data items in a transaction. Many business organizations share data with others, outsource their business data for specific business solution. In these situations, the sensitive information leakage is the biggest problem. Strong and efficient privacy preserving techniques are needed to secure organization's data during third party sharing. In this paper, a comprehensive study of various methods for privacy preservation is presented which evaluates and analyzes various techniques for maintaining privacy during association rule mining process. Moreover, paper also prospects the development of privacy preservation for future applications.

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Index Terms

Computer Science
Information Sciences


Association rule mining ARM Privacy Preservation Data Sanitization Data Distortion Data Perturbation Cryptography Frequent Patterns