Privacy Preserving Data Mining: Case of Association Rules

Provided by: International Journal of Computer Science Issues
Topic: Security
Format: PDF
Data mining has become an important technology to discover a hidden and nontrivial knowledge from large amounts of data. A major problem is to achieve this discovery process with preserving privacy of extracted data and/or knowledge. Privacy Preserving Data Mining (PPDM) is a new area of research that studies the side effects of knowledge mining methods on individuals and organizations privacy. The authors present in this paper a state of the art of the PPDM in the case of association rules. They propose taxonomy of existing techniques and a classification of work realized in this paper.

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