Privacy Preservation in Utility Mining Based on Genetic Algorithm: A New Approach

Abstract

Privacy preservation in data mining tends to protect the sensitive information from getting exploited by the nefarious users in a huge database. This paper explains the concepts of utility-based privacy mining approach using genetic algorithm for optimized computing and search to enhance security and confidentiality. A brief classification and comparison of PPDM (Privacy Preservation in Data Mining) techniques are also listed along with the techniques and the pros and cons of utility mining techniques. To hide the sensitive information, many approaches have been proposed. In this study, we propose an efficient method, for protecting high utility itemsets using genetic approach to achieve the privacy with balance between privacy and disclosure of information. The basic idea behind is to use the proposed work to enhance effectiveness measurements with certain parameters.