tag: Differential-Privacy · 2 items
- Engineer — Learn: The paper exposes a fundamental flaw in sample-and-scale DP noise protocols, achieving near-100% membership-inference success against Orchard and DP-BREM+; engineers building federated analytics or DP aggregation pipelines should audit whether their noise-sampling implementation uses the vulnerable scaling approach.
- SOC/IR — Skip
- Leader — Skip
- Engineer — Learn: If you rely on DP guarantees to protect training data in ML pipelines, this research shows that controlling memorization and controlling extraction are formally separate — a model can be memorized yet unextractable, or vice versa. Revisit your threat model assumptions, but no system change is required today.
- SOC/IR — Skip
- Leader — Skip