Relative Privacy Threats and Learning From Anonymized Data

We consider group-based anonymization schemes, a popular approach to data publishing. This approach aims at protecting privacy of the individuals involved in a dataset, by releasing an obfuscated version of the original data, where the exact correspondence between individuals and attribute values is...

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Veröffentlicht in:	IEEE transactions on information forensics and security 2020, Vol.15, p.1379-1393
Hauptverfasser:	Boreale, Michele, Corradi, Fabio, Viscardi, Cecilia
Format:	Artikel
Sprache:	eng
Schlagworte:	anonymization Data privacy Datasets Diseases Heart k-anonymity mcmc methods Privacy Publishing Risk analysis Sociology Statistics Threat evaluation
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