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USENIX Security '21 - Systematic Evaluation of Privacy Risks of Machine Learning Models
Quantifying Privacy Risks of Machine Learning Models (Yang Zhang, CISPA)
USENIX Security '21 - MPInspector: A Systematic and Automatic Approach for Evaluating the Security
Yang Zhang - Quantifying Privacy Risks of Machine Learning Models
USENIX Security '21 - Where's Crypto?: Automated Identification and Classification of Proprietary...
USENIX Security '21 - Reducing Bias in Modeling Real-world Password Strength via Deep Learning...
USENIX Security '21 - Stealing Links from Graph Neural Networks
USENIX Security '16 - Stealing Machine Learning Models via Prediction APIs
Inference Risks for Machine Learning (ICLR Workshop on Distributed and Private Machine Learning)
PEPR '23 - The Missing Link in Privacy Risk Assessments
OpML '20 (Short) - Automating Operations with ML
USENIX Security '15 - SecGraph: A Uniform and Open-source Evaluation System for Graph Data...
