CFP last date
20 June 2024
Reseach Article

Hybrid Approach to Association Rule Hiding

Published on April 2015 by S.sangeetha, R. Kiruba
National Conference on Information Processing and Remote Computing
Foundation of Computer Science USA
NCIPRC2015 - Number 2
April 2015
Authors: S.sangeetha, R. Kiruba
0374be9f-d516-420e-a0cb-5b04256af9df

S.sangeetha, R. Kiruba . Hybrid Approach to Association Rule Hiding. National Conference on Information Processing and Remote Computing. NCIPRC2015, 2 (April 2015), 17-23.

@article{
author = { S.sangeetha, R. Kiruba },
title = { Hybrid Approach to Association Rule Hiding },
journal = { National Conference on Information Processing and Remote Computing },
issue_date = { April 2015 },
volume = { NCIPRC2015 },
number = { 2 },
month = { April },
year = { 2015 },
issn = 0975-8887,
pages = { 17-23 },
numpages = 7,
url = { /proceedings/nciprc2015/number2/20512-8013/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Information Processing and Remote Computing
%A S.sangeetha
%A R. Kiruba
%T Hybrid Approach to Association Rule Hiding
%J National Conference on Information Processing and Remote Computing
%@ 0975-8887
%V NCIPRC2015
%N 2
%P 17-23
%D 2015
%I International Journal of Computer Applications
Abstract

Data mining is a technique for summarizing and identifying similar patterns in data. Data mining can take different approaches and build different models depending upon the type of data involved and the objectives. In this Paper we follow the association rules approach for finding the correlation relationships among large set of data items. The rules are generated in order to hide the sensitive rules which are highly confidential by using DSR (Decrease support value of Right Hand Side) approach and PSO (Particle Swarm Optimization) approach. In this paper we propose a new algorithm called HYBRID algorithm. The objective of this paper is to reduce the side effects such as ghost rule and lost rule and number of modification and to increase the hiding ratio by hybrid approach which is achieved by combination of DSR & PSO. Experimental results of the proposed approach demonstrate the efficient information hiding with fewer side effects and modifications.

References
  1. Rajan Chattamvelli, "Data mining methods", published by Narosa publishing house in the year 2009
  2. Yi-Hung Wu, Chia-Ming Chiang, and Arbee L. P. Chen, Senior Member, IEEE Computer Society, "Hiding Sensitive Association Rules with Limited Side Effects, IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, VOL. 19, NO. 1, JANUARY 2007
  3. 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.
  4. https://archive. ics. uci. edu/ml/datasets/Breast+Cancer+Wisconsin+(Original)
  5. Dr. Duraiswamy. K, Dr. Manjula. D, and Maheswari. N "A New Approach to Sensitive Rule Hiding", ccsenet journal, vol 1, No. 3, August, 107-111
Index Terms

Computer Science
Information Sciences

Keywords

Item Sets Data Mining Association Rules Privacy Preservation Dsr Approach Pso Approach Hybrid.