Research Article
Privacy Preservation using Association Rule Mining with Limited Side Effect
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 49 - Issue 20 |
| Published: July 2012 |
| Authors: Deepti Gatne, S. S. Sane, Manoj Jhade |
10.5120/7885-1113
|
Deepti Gatne, S. S. Sane, Manoj Jhade . Privacy Preservation using Association Rule Mining with Limited Side Effect. International Journal of Computer Applications. 49, 20 (July 2012), 9-12. DOI=10.5120/7885-1113
@article{ 10.5120/7885-1113,
author = { Deepti Gatne,S. S. Sane,Manoj Jhade },
title = { Privacy Preservation using Association Rule Mining with Limited Side Effect },
journal = { International Journal of Computer Applications },
year = { 2012 },
volume = { 49 },
number = { 20 },
pages = { 9-12 },
doi = { 10.5120/7885-1113 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2012
%A Deepti Gatne
%A S. S. Sane
%A Manoj Jhade
%T Privacy Preservation using Association Rule Mining with Limited Side Effect%T
%J International Journal of Computer Applications
%V 49
%N 20
%P 9-12
%R 10.5120/7885-1113
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The privacy preservation using association rule mining is the base of this research. The concept of privacy preserving data mining has been proposed in response to the concerns of preserving personal information from data mining algorithms. The proposed method focuses on minimizing side effects caused by privacy preservation techniques. Side effects are loss of rules and generation of the false rules. One of the techniques in privacy preservation selectively modifies individual values from a database to prevent the discovery of a set of rules. There are two known algorithms for it, ISL (Increase Support of Left) and DSR (Decrease Support of Right). Since ISL & DSR techniques aim at hiding all sensitive rules, they cannot avoid the undesired side effects. ISL algorithm results in false rules generation where DSR results in loss of rules. The propose system suggest modification to both of these algorithms in such a way that output is generated with limited side effects. Also it takes the decision about which algorithm to be used to hide a specific rule.
References
- Tinghuai Ma, Sainan "Privacy Preserving Based on Association Rule Mining" Wang School of Computer & Software Nanjing University of Information Science & Technology Nanjing, China thma@nuist. edu. cn
- Yi-Hung Wu, Chia-Ming Chiang, and Arbee L. P. Chen, "Hiding Sensitive Association Rules with Limited Side Effects" Senior Member, IEEE Computer Society
- Ila Chandrakar, Yelipe Usha Rani, Mortha Manasa and Kondabala Renuk "Hybrid Algorithm for Privacy Preserving Association Rule Mining" Department of Information Technology,VNR Vignana Jyothi Institute of Engineering and Technology, Hyderabad, India.
- Chris Clifton, Murat Kantarcioglou ,Xiadong Lin. "Tools for privacy preserving distributed data mining. " SIGKDD Explorations, 2003, 4(2):28-3
- PEI-JI WANG "MINING ASSOCIATION RULES BASED ON APRIORI ALGORITHM AND APPLICATION"
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