Synthetic Data—Anonymisation Groundhog Day¶
Stadler, T., Oprisanu, B., & Troncoso, C. (2022). Synthetic Data—Anonymisation Groundhog Day. 31st USENIX Security Symposium, 1451-1468.
Cited by¶
1 citation across 1 artifact.
Each citation links to the sentence it supports in the citing article.
Mechanisms¶
- Synthetic or Perturbed Data Validation
- The discipline is to fix the utility purpose and the leakage thresholds before seeing the candidate, and to treat the battery as a floor that grows as new reconstruction routes are found.
This sourcePresents a modular synthetic-data privacy evaluation framework that can be extended to additional privacy concerns and attacks.
- The discipline is to fix the utility purpose and the leakage thresholds before seeing the candidate, and to treat the battery as a floor that grows as new reconstruction routes are found.
Verification¶
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Registry ID ref:e011ece232c4 · see in the full table