Document - Data anonimity meets non-discrimination

2013

Conference article Open Access

Data anonimity meets non-discrimination

Ruggieri S

Privacy Discrimination H.2.8 Database Applications

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.

Publisher: IEEE

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@inproceedings{oai:it.cnr:prodotti:326360,
	title = {Data anonimity meets non-discrimination},
	author = {Ruggieri S},
	publisher = {IEEE},
	doi = {10.1109/icdmw.2013.56},
	year = {2013}
}