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HọRegression modelMachine learning
Năm ra đời19892006
Người khởi xướngGeorge Duncan & Diane LambertCynthia Dwork
LoạiProbabilistic risk modelPrivacy-preserving randomized mechanism
Công trình gốcDuncan, G. T., & Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business & Economic Statistics, 7(2), 207–217. DOI ↗Dwork, C. (2006). Differential privacy. International Colloquium on Automata, Languages and Programming (ICALP), 1–12. DOI ↗
Tên gọi khácMicrodata Disclosure Risk, Statistical Disclosure Control Risk Estimation, Istatistiksel Açıklama Riski Değerlendirmesi, Re-identification Risk AssessmentDP, epsilon-differential privacy, randomized privacy, Diferansiyel Gizlilik
Liên quan33
Tóm tắtDisclosure 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.Differential privacy is a mathematical framework for releasing statistical information about a dataset while providing rigorous guarantees that individual records cannot be identified or inferred. Introduced by Cynthia Dwork in 2006, it formalizes privacy as a probabilistic bound: any single individual's presence or absence in the dataset changes the output distribution by at most a multiplicative factor of e^ε, where ε is the privacy budget controlling the privacy–utility tradeoff.
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ScholarGateSo sánh phương pháp: Disclosure Risk Assessment · Differential Privacy. Truy cập ngày 2026-06-19 từ https://scholargate.app/vi/compare