Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Tathmini ya Hatari ya Ufunuo× | k-Uthibitisho: Kulinda Faragha ya Mtu Binafsi katika Data Iliyotolewa× | |
|---|---|---|
| Nyanja | Faragha | Faragha |
| Familia≠ | Regression model | Machine learning |
| Mwaka wa asili≠ | 1989 | 2002 |
| Mwanzilishi≠ | George Duncan & Diane Lambert | Latanya Sweeney |
| Aina≠ | Probabilistic risk model | Privacy-preserving data transformation |
| Chanzo asilia≠ | Duncan, G. T., & Lambert, D. (1989). The risk of disclosure for microdata. Journal of Business & Economic Statistics, 7(2), 207–217. DOI ↗ | Sweeney, L. (2002). k-anonymity: A model for protecting privacy. International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, 10(5), 557–570. DOI ↗ |
| Majina mbadala | 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 |
| Zinazohusiana≠ | 3 | 2 |
| Muhtasari≠ | 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. |
| ScholarGateSeti ya data ↗ |
|
|