Comparer des méthodes

	Évaluation du risque de divulgation	k-Anonymity : Protection de la vie privée individuelle dans les données publiées
Domaine	Protection de la vie privée	Protection de la vie privée
Famille	Regression model	Machine learning
Année d'origine	1989	2002
Auteur d'origine	George Duncan & Diane Lambert	Latanya Sweeney
Type	Probabilistic risk model	Privacy-preserving data transformation
Source fondatrice	Duncan, G. T., & Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business & Economic Statistics, 7(2), 207–217.	Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5), 557–570.
Alias	Microdata Disclosure Risk, Statistical Disclosure Control Risk Estimation, Istatistiksel Açıklama Riski Değerlendirmesi, Re-identification Risk Assessment	k-Anonymization, k-Anonymous Microdata, Quasi-Identifier Suppression Model, k-Anonimlik
Apparentées	3	2
Résumé	Disclosure Risk Assessment is a probabilistic framework introduced by Duncan and Lambert (1989) for quantifying how likely it is that releasing microdata — individual-level records from surveys or administrative files — will allow an outside party to identify a specific respondent or infer sensitive attributes. It is used by statistical agencies, data custodians, and researchers charged with protecting confidentiality before any public release of person-level datasets.	k-Anonymity is a formal privacy model introduced by Latanya Sweeney in 2002 to protect individuals when personal data is released for research or public use. It requires that every record in a published dataset be indistinguishable from at least k−1 other records with respect to a designated set of quasi-identifying attributes — such as age, gender, and ZIP code — preventing re-identification by linking released data to external sources.