Feature Creation based Slicing for Privacy Preserving Data Mining
Author:
Affiliation:
1. Dept. of Computer Science & Engg Avinashilingam University for Women, Coimbatore, India
2. Dept. of Computer Science & Engg Government College of Technology, Coimbatore, India
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/2888451.2888462
Reference35 articles.
1. ACHIEVING k-ANONYMITY PRIVACY PROTECTION USING GENERALIZATION AND SUPPRESSION
2. On the Anonymization of Sparse High-Dimensional Data
3. Information fusion in data privacy: A survey
4. Aggarwal C.C. and Philip S.Y. 2008. An introduction to privacy-preserving data mining. In Privacy-preserving data mining. pp. 1--9. Springer US. Aggarwal C.C. and Philip S.Y. 2008. An introduction to privacy-preserving data mining. In Privacy-preserving data mining. pp. 1--9. Springer US.
5. Aggarwal C.C. and Philip S.Y. 2008. A general survey of privacy-preserving data mining models and algorithms. pp. 11--52. Springer US. Aggarwal C.C. and Philip S.Y. 2008. A general survey of privacy-preserving data mining models and algorithms. pp. 11--52. Springer US.
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1. Feature Based Data Anonymization with Slicing Method for Data Publishing;Proceedings of the 2019 11th International Conference on Machine Learning and Computing - ICMLC '19;2019
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