Title :
Protecting sensitive knowledge by data sanitization
Author :
Oliveira, Stanley R M ; Zaïane, Osmar R.
Author_Institution :
Embrapa Informatica Agropecuaria, Campinas, Brazil
Abstract :
We address the problem of protecting some sensitive knowledge in transactional databases. The challenge is on protecting actionable knowledge for strategic decisions, but at the same time not losing the great benefit of association rule mining. To accomplish that, we introduce a new, efficient one-scan algorithm that meets privacy protection and accuracy in association rule mining, without putting at risk the effectiveness of the data mining per se.
Keywords :
associative processing; data mining; data privacy; transaction processing; very large databases; association rule mining; data mining; data sanitization; one-scan algorithm; sensitive knowledge privacy protection; strategic decisions; transactional databases; Association rules; Collaboration; Data mining; Data privacy; Data security; Information analysis; Information security; NP-hard problem; Protection; Transaction databases;
Conference_Titel :
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN :
0-7695-1978-4
DOI :
10.1109/ICDM.2003.1250990
