Comprehensive Privacy Analysis of Deep Learning

Comprehensive Privacy Analysis of Deep Learning Milad Nasr Presented at the 2019 IEEE Symposium on Security Privacy May 2022, 2019 San Francisco, CA Deep neural networks are susceptible to various inference attacks as they remember information about their training data. We design whitebox inference attacks to perform a comprehensive privacy analysis of deep learning models. We measure the privacy leakage through parameters of fully trained models as