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- Dwork and Roth. Algorithmic Foundations of Differential Privacy.
- Boneh and Shoup. A Graduate Course in Applied Cryptography.
- Evans, Kolesnikov, and Rosulek. A Pragmatic Introduction to Secure Multi-Party Computation.
- Barocas, Hardt, and Narayanan. Fairness and Machine Learning.
- CSE 291: Language-Based Security (Deian Stefan, UC San Diego)
- CSE 711: Topics in Differential Privacy (Marco Gaboardi, University at Buffalo)
- CS 800: The Algorithmic Foundations of Data Privacy (Aaron Roth, UPenn)
- CS 229r: Mathematical Approaches to Data Privacy (Salil Vadhan, Harvard)
- CS 294: Fairness in Machine Learning (Moritz Hardt, UC Berkeley)
- CS 598: Special Topics in Adversarial Machine Learning (Bo Li, UIUC)