State of the art in Privacy Preserving Data MiningFunded under: FP7-ICT
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.
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)
Record Number: 200910507 / Last updated on: 2009-12-11
Original language: en
Available languages: en