State of the Art in Privacy Preserving Data Mining
Privacy is one of the most important properties an information system must satisfy. A relatively new trend shows that classical
access control techniques are not sufficient to guarantee privacy when Data Mining techniques are used. Such a trend, especially in the context of public databases, or in the context of sensible information related to critical infrastructures, represents, nowadays a not negligible thread. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of modifying the database in such a way to prevent the discovery of sensible information. This is a very complex task and there exist in the scientific literature some different approaches to the problem. In this work we present a "Survey" of the current PPDM methodologies which seem promising for the future.
NAI FOVINO Igor;
MASERA Marcelo;
2008-01-22
OPOCE
JRC42698
1018-5593,
EUR 23068 EN,
https://publications.jrc.ec.europa.eu/repository/handle/JRC42698,
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