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開示リスク評価×差分プライバシー×
分野プライバシープライバシー
系統Regression modelMachine learning
提唱年19892006
提唱者George Duncan & Diane LambertCynthia Dwork
種類Probabilistic risk modelPrivacy-preserving randomized mechanism
原典Duncan, 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 ↗
別名Microdata Disclosure Risk, Statistical Disclosure Control Risk Estimation, Istatistiksel Açıklama Riski Değerlendirmesi, Re-identification Risk AssessmentDP, epsilon-differential privacy, randomized privacy, Diferansiyel Gizlilik
関連33
概要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.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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ScholarGate手法を比較: Disclosure Risk Assessment · Differential Privacy. 2026-06-18に以下より取得 https://scholargate.app/ja/compare