পদ্ধতির তুলনা করুন

	প্রকাশের ঝুঁকি মূল্যায়ন	ডিফারেনশিয়াল প্রাইভেসি
ক্ষেত্র	গোপনীয়তা	গোপনীয়তা
পরিবার	Regression model	Machine learning
উদ্ভবের বছর	1989	2006
প্রবর্তক	George Duncan & Diane Lambert	Cynthia Dwork
ধরন	Probabilistic risk model	Privacy-preserving randomized mechanism
মৌলিক উৎস	Duncan, G. T., & Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business & Economic Statistics, 7(2), 207–217.	Dwork, C. (2006). Differential privacy. International Colloquium on Automata, Languages and Programming (ICALP), 1–12.
অপর নাম	Microdata Disclosure Risk, Statistical Disclosure Control Risk Estimation, Istatistiksel Açıklama Riski Değerlendirmesi, Re-identification Risk Assessment	DP, epsilon-differential privacy, randomized privacy, Diferansiyel Gizlilik
সম্পর্কিত	3	3
সারসংক্ষেপ	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.