PUMA
Istituto di Scienza e Tecnologie dell'Informazione     
Ruggieri S. Data anonimity meets non-discrimination. In: ICDMW 2013 - IEEE 13th International Conference on Data Mining Workshops (Dallas, Texas, 7-10 December 2013). Proceedings, pp. 875 - 882. IEEE, 2013.
 
 
Abstract
(English)
We investigate the relation between t-closeness, a well-known model of data anonymization, and alpha-protection, a model of data discrimination. We show that t-closeness implies bd(t)-protection, for a bound function bd() depending on the discrimination measure at hand. This allows us to adapt an inference control method, the Mondrian multidimensional generalization technique, to the purpose of non-discrimination data protection. The parallel between the two analytical models raises intriguing issues on the interplay between data anonymization and nondiscrimination research in data mining.
URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6754013
DOI: 10.1109/ICDMW.2013.56
Subject Privacy
Discrimination
H.2.8 Database Applications
68U99


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