Indian Journal of Science and Technology
Year: 2016, Volume: 9, Issue: 3, Pages: 1-8
R. Hariharan*, C. Mahesh, P. Prasenna and R. Vinoth Kumar
*Author For Correspondence
Department of Information Technology, Vel Tech University, Chennai - 600062, Tamil Nadu, India;
Email: [email protected]
Background/Objectives: Privacy preservation in data mining to hold back the sensitive data from attackers. Findings: There are various existing methods available to preserve the data like perturbation, anonymization, randomization etc., each method has its own advantages and disadvantages. The trade-off between security and utility of data should be handled with standardizing methods for the PPDM. In this paper explained a method based on PPDM in data mining using cluster based greedy method. Application/Improvements: This method can be applied in sensitive data areas such as hospitals, Customer Management System, government survey, etc., where there is need for privacy preservation.
Keywords: Cluster based Greedy Method, Classification Error, Isometric Transformation, Privacy Preservation, Privacy Preservation Rate
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