Protecting Sensitive Knowledge By Data Sanitization
- Stanley R. Oliveira
- Osmar R. Zaiane, University of Alberta (Database)
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
S. Oliveira, O. Zaiane. "Protecting Sensitive Knowledge By Data Sanitization". IEEE International Conference on Data Mining (ICDM), Melbourne, USA, pp 613-616, November 2003.| Keywords: | |
| Category: | In Conference |
| Web Links: | Webdocs |
BibTeX
@incollection{Oliveira+Zaiane:ICDM03,
author = {Stanley R. Oliveira and Osmar R. Zaiane},
title = {Protecting Sensitive Knowledge By Data Sanitization},
Pages = {613-616},
booktitle = {IEEE International Conference on Data Mining (ICDM)},
year = 2003,
}Last Updated: February 03, 2020Submitted by Sabina P
