期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2011
卷号：32
期号：2
页码：118-122
出版社：Journal of Theoretical and Applied
摘要：Extracting previously unknown patterns from huge volume of data is the primary objective of any data mining algorithm. In recent days there is a tremendous growth in data collection due to the advancement in the field of information technology. The patterns revealed by data mining algorithm can be used in various domains like Image Analysis, Marketing and weather forecasting. As a side effect of the mining algorithm some sensitive information is also revealed. There is a need to preserve the privacy of individuals which can be achieved by using privacy preserving data mining. In this paper we propose a new approach to preserve sensitive information using fuzzy logic. First we perform clustering on the original data set then we add noise to the numeric data using a fuzzy membership function that results in distorted data. Set of Clusters generated using the distorted data is also relative to the original cluster as well as privacy is also achieved. It is also proved that the number of iterations for performing the clustering process is less in our approach when compared with the traditional approach.
