Optimized key generation-based privacy preserving data mining model for secure data publishing

Abstract

The data from the mobile devices and internet services plays a significant role now a day. The information shared needs to be original to get the best solution. Without the utilization of privacy preservation techniques, the individual's sensitive information cannot be exposed. The Privacy preserving data publishing (PPDP) is one of the privacy preserving techniques to preserve privacy. However, the reduction of the loss of data and the security enhancement are the major challenges. To solve the issues in secure data publishing, the efficient Cat Swarm Henry Gas Solubility Optimization (CSHGSO) is introduced for achieving effective privacy preservation for secure data publishing. In addition, the proposed CSHGSO is devised by the incorporation of Cat Swarm Optimization (CSO), and Henry Gas Solubility Optimization (HGSO). Here, the procedure of generating secret key is carried out based on the proposed CSHGSO with respect to the objective measures. The experimentation of the developed CSHGSO is performed in JAVA tool using Heart Disease Dataset. Furthermore, the CSHGSO achieved the higher conditional privacy of 1.338 using database-1, maximum accuracy of 0.965 using database-4, and the NMI value of 0.927 using database-4.