Information Driven Association Rule Hiding Algorithms

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.

NAI FOVINO Igor;  TROMBETTA Alberto; 

2008-11-05

IEEE

JRC43963

http://www.ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=4621664&isnumber=4621577,    https://publications.jrc.ec.europa.eu/repository/handle/JRC43963,