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Protecting data: a fuzzy approach. (English) Zbl 1343.68076

Summary: Privacy issues represent a longstanding problem nowadays. Measures such as \(k\)-anonymity, \(l\)-diversity and \(t\)-closeness are among the most used ways to protect released data. This work proposes to extend these three measures when the data are protected using fuzzy sets instead of intervals or representative elements. The proposed approach is then tested using Energy Information Authority data set and different fuzzy partition methods. Results shows an improvement in protecting data when data are encoded using fuzzy sets.

MSC:

68P25 Data encryption (aspects in computer science)
03E72 Theory of fuzzy sets, etc.
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