DETECTIVE: a decision tree based categorical value clustering and perturbation technique for preserving privacy in data mining

@article{Islam2005DETECTIVEAD,
  title={DETECTIVE: a decision tree based categorical value clustering and perturbation technique for preserving privacy in data mining},
  author={M. Z. Islam and Ljiljana Brankovic},
  journal={INDIN '05. 2005 3rd IEEE International Conference on Industrial Informatics, 2005.},
  year={2005},
  pages={701-708}
}
Data mining is a powerful tool for information discovery from huge datasets. Various sectors, including commercial, government, financial, medical, and scientific, are applying data mining techniques on their datasets that typically contain sensitive individual information. During this process the datasets get exposed to several parties, which can potentially lead to disclosure of sensitive information and thus to breaches of privacy. Several data mining privacy preserving techniques have been… CONTINUE READING
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A Framework for Privacy Preserving Classification in Data Mining

M.Z.Islam, L. Brankovic
Proceedings of Australasian Workshop on Data Mining and Web Intelligence (DMWI • 2004
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Privacy-Preserving Data Mining

SIGMOD Conference • 2000
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