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