Protecting Sensitive Knowledge By Data Sanitization

I
ICDM
2003
Third IEEE International Conference on Data Mining (ICDM'03)
Abstract - Protecting Sensitive Knowledge By Data Sanitization

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	Similar Articles Articles by Stanley R. M. Oliveira Articles by Osmar R. Za?ane

Third IEEE International Conference on Data Mining (ICDM'03)

Melbourne, Florida

November 19-November 22

ISBN: 0-7695-1978-4

	ASCII Text	x
	Stanley R. M. Oliveira, Osmar R. Za?ane, "Protecting Sensitive Knowledge By Data Sanitization," Data Mining, IEEE International Conference on, pp. 613, Third IEEE International Conference on Data Mining (ICDM'03), 2003.

	BibTex	x
	@article{ 10.1109/ICDM.2003.1250990, author = {Stanley R. M. Oliveira and Osmar R. Za?ane}, title = {Protecting Sensitive Knowledge By Data Sanitization}, journal ={Data Mining, IEEE International Conference on}, volume = {0}, year = {2003}, isbn = {0-7695-1978-4}, pages = {613}, doi = {http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250990}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Data Mining, IEEE International Conference on TI - Protecting Sensitive Knowledge By Data Sanitization SN - 0-7695-1978-4 SP EP A1 - Stanley R. M. Oliveira, A1 - Osmar R. Za?ane, PY - 2003 KW - null VL - 0 JA - Data Mining, IEEE International Conference on ER -

Stanley R. M. Oliveira, Embrapa Inform?tica Agropecu?ria, Campinas, Brasil

Osmar R. Za?ane, University of Alberta, Edmonton, Canada

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ICDM.2003.1250990

In this paper, 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.

Citation:

Stanley R. M. Oliveira, Osmar R. Za?ane, "Protecting Sensitive Knowledge By Data Sanitization," icdm, pp.613, Third IEEE International Conference on Data Mining (ICDM'03), 2003

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