ML privacy
PrivacyRaven
Privacy-testing library for deep-learning systems and privacy-preserving ML techniques.
View on GitHub
trailofbits/privacyraven
Best for
Measuring whether a model leaks more than a team expects.
Surface
ML privacy
Catalog group
Protect Python, packaging, and ML-heavy workflows
Repository
trailofbits/privacyraven
From the README
Note: This project is on hiatus. PrivacyRaven is a privacy testing library for deep learning systems. You can use it to determine the susceptibility of a model to different privacy attacks; evaluate privacy preserving machine learning techniques; develop novel privacy metrics and attacks; and repurpose attacks for data provenance and other use cases.Read the full README on GitHub ↗
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