HIDING THE SENSITIVE RULES WITH MINIMUM CONSTRAINTS OF DATA PUBLISHING IN SIPRP METHOD

Recently, motivating the demand for the privacy and secure data mining research is the expansion of techniques that include the privacy and security along with effective data publishing. Most of the research work is developed for data distribution with privacy. However, the protocols used in the homomorphic encryption increased the computational costs and communication. In order to overcome the limitations, a Swarm optimization and Iterative Privacy Rule Preservation (SIPRP) method is designed in the paper to improve the efficiency of the privacy preserving association rule mining with the constraint minimization. Initially, SIPRP method generates the association rules for the privacy preserving distribution database based on the support and confidence threshold. Then, the sensitive rules associated with the optimal sensitive items which are hidden are evaluated. After that, the sensitive rules are subjected to the Particle Swarm Optimization (PSO) for hiding and preserving highly confidential privacy rules. Finally, the SIPRP method obtains the sensitive sets of items for generating the specific sensitive rules. It is hidden with less effect on the privacy being exposed during the data distribution across multiple users.