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Hybrid Approach to Association Rule Hiding

IJCA Proceedings on National Conference on Information Processing and Remote Computing
© 2015 by IJCA Journal
NCIPRC 2015 - Number 2
Year of Publication: 2015
S. Sangeetha
R. Kiruba

S.sangeetha and R Kiruba. Article: Hybrid Approach to Association Rule Hiding. IJCA Proceedings on National Conference on Information Processing and Remote Computing NCIPRC 2015(2):17-23, April 2015. Full text available. BibTeX

	author = {S.sangeetha and R. Kiruba},
	title = {Article: Hybrid Approach to Association Rule Hiding},
	journal = {IJCA Proceedings on National Conference on Information Processing and Remote Computing},
	year = {2015},
	volume = {NCIPRC 2015},
	number = {2},
	pages = {17-23},
	month = {April},
	note = {Full text available}


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.


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