Name
Title | ||
|---|---|---|
Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data |
Abstract | ||
|---|---|---|
Partially synthetic data comprise the units originally surveyed with some collected values, such as sensitive values at high risk of disclosure or values of key identifiers, replaced with multiple draws from statistical models. Because the original records remain on the file, intruders may be able to link those records to external databases, even though values are synthesized. We illustrate how statistical agencies can evaluate the risks of identification disclosures before releasing such data. We compute risk measures when intruders know who is in the sample and when the intruders do not know who is in the sample. We use classification and regression trees to synthesize data from the U.S. Current Population Survey. |
Year | DOI | Venue |
|---|---|---|
2008 | 10.1007/978-3-540-87471-3_19 | Privacy in Statistical Databases |
Keywords | Field | DocType |
intruder uncertainty,partially synthetic data,synthetic data.,cart,risk measure,high risk,estimating identification disclosure risks,key identifiers,risk,u.s. current population survey,multiple draw,identification disclosure,statistical model,disclosure,synthetic data,statistical agency,external databases | Current Population Survey,Data mining,Identifier,Regression,Computer science,Synthetic data,Statistical model,Sampling (statistics),Statistics | Conference |
Volume | ISSN | Citations |
5262 | 0302-9743 | 11 |
PageRank | References | Authors |
1.02 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jörg Drechsler | 1 | 39 | 5.15 |
| Jerome P. Reiter | 2 | 216 | 22.12 |