Title: Privacy Preserving Data Mining, A Data Quality Approach
Authors: NAI FOVINO IGORMASERA MARCELO
Publisher: OPOCE
Publication Year: 2008
JRC N°: JRC42700
ISSN: 1018-5593
Other Identifiers: EUR 23070 EN
URI: http://publications.jrc.ec.europa.eu/repository/handle/JRC42700
Type: EUR - Scientific and Technical Research Reports
Abstract: 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 datamining techniques are used. Privacy Preserving Data Mining (PPDM) algorithms have been recently introduced with the aim of sanitizing the database in such a way to prevent the discovery of sensible information (e.g. association rules). A drawback of such algorithms is that the introduced sanitization may disrupt the quality of data itself. In this report we introduce a new methodology and algorithms for performing useful PPDM operations, while preserving the data quality of the underlying database.
JRC Institute:Institute for the Protection and Security of the Citizen

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