Swarm Optimization and Iterative Privacy Generates Asensitive Rule with Theconstraints Data

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 the effective data publishing. Most of the research work is developed for the data distribution with the privacy. However, the protocols used in the homomorphic encryption which 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. Finally, the SIPRP method obtains the sensitive sets of items for generating the specific sensitive. Experimental evaluation of the SIPRP method is done with the performance metrics such as the number of sensitive rule.