Anonymity: An Assessment and Perspective in Privacy Preserving Data Mining

Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
Privacy preserving data mining techniques depends on privacy, which captures what information is sensitive in the original data and should therefore be protected from either direct or indirect disclosure. Secrecy and anonymity are useful ways of thinking about privacy. This privacy should be measureable and entity to be considered private should be valuable. In this paper, the authors discuss the various anonymization techniques that can be used for privatizing data. The goal of anonymization is to secure access to confidential information while at the same time releasing aggregate information to the public.

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