Audit finds DP violations in 5 of 9 mechanisms in Apple's framework due to insecure floating-point samplers and disabled local DP in secure aggregation, impacting 87% of macOS Sonoma and 68% of Sequoia data collection.
Tight auditing of differentially private machine learning,
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.CR 2representative citing papers
SnapAudit decomposes DP-ICL into a deterministic snapshot stage and a stochastic noise stage, using bootstrap simulation to achieve 80-200x faster auditing and exposing privacy bound violations in existing Gaussian and embedding mechanisms.
citing papers explorer
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Auditing Apple's DifferentialPrivacy.framework: Implementation Bugs, Misconfigurations, and Practical Risks
Audit finds DP violations in 5 of 9 mechanisms in Apple's framework due to insecure floating-point samplers and disabled local DP in secure aggregation, impacting 87% of macOS Sonoma and 68% of Sequoia data collection.
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SnapAudit: Active Auditing of Differentially Private In-Context Learning via Snapshot-Based Simulation
SnapAudit decomposes DP-ICL into a deterministic snapshot stage and a stochastic noise stage, using bootstrap simulation to achieve 80-200x faster auditing and exposing privacy bound violations in existing Gaussian and embedding mechanisms.