A Novel Approach for Privacy Preserving Publication of Data

Protecting privacy of an individual while revealing knowledge about one's personal and sensitive information is a much talked about concern in the data mining world. Several works have been reported in literature as a solution to this concern. But most of these solutions which claim privacy preserving, usually end up with less information in the resulting data. The tradeoff in information compromised for privacy is very large. In this paper, the authors present a fuzzy and taxonomy tree based solution where optimal and useful knowledge about individual's information can be retained while preserving privacy of that individual.