Community Research and Development Information Service - CORDIS

FP7

State of the art in Privacy Preserving Data Mining

Funded under: FP7-ICT

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 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.

Additional information

Authors: NAI FOVINO I, European Commission, Joint Research Centre, Institute for the Protection and the Security of the Citizen, Ispra (IT);MASERA M, European Commission, Joint Research Centre, Institute for the Protection and the Security of the Citizen, Ispra (IT)
Bibliographic Reference: EUR 23068 EN (2008) 51pp Free of charge
Availability: http://bookshop.europa.eu/is-bin/INTERSHOP.enfinity/WFS/EU-Bookshop-Site/en_GB/-/EUR/ViewPublication-Start?PublicationKey=LBNA23068 (Catalogue Number: LB-NA-23068-EN-C)
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