DocumentCode
2370708
Title
Protecting sensitive knowledge by data sanitization
Author
Oliveira, Stanley R M ; Zaïane, Osmar R.
Author_Institution
Embrapa Informatica Agropecuaria, Campinas, Brazil
fYear
2003
fDate
19-22 Nov. 2003
Firstpage
613
Lastpage
616
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;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Mining, 2003. ICDM 2003. Third IEEE International Conference on
Print_ISBN
0-7695-1978-4
Type
conf
DOI
10.1109/ICDM.2003.1250990
Filename
1250990
Link To Document