Please use this identifier to cite or link to this item:
|Title:||Information Driven Association Rule Hiding Algorithms|
|Authors:||NAI FOVINO IGOR; TROMBETTA Alberto|
|Citation:||Proceedings of the 2008 1st International Conference on Information Technology IT 2008 p. 383-387|
|Type:||Articles in periodicals and books|
|Abstract:||Privacy is one of the most important properties an informa- tion system must satisfy. A relatively new trend shows that classical ac- cess control techniques are not sufficient to guarantee privacy when data- mining 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 intro- duced sanitization may disrupt the quality of data itself. In this paper we introduce a new methodology and algorithms for performing useful PPDM operations, while preserving the data quality of the underlying database.|
|JRC Institute:||Space, Security and Migration|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.