本课程首先介绍了机器学习、安全、隐私、对抗性机器学习和博弈论等主题。然后从研究的角度，讨论各个课题和相关工作的新颖性和潜在的拓展性。通过一系列的阅读和项目，学生将了解不同的机器学习算法，并分析它们的实现和安全漏洞，并培养开展相关主题的研究项目的能力。

https://aisecure.github.io/TEACHING/2020_fall.html

Evasion Attacks Against Machine Learning Models (Against Classifiers) Evasion Attacks Against Machine Learning Models (Non-traditional Attacks) Evasion Attacks Against Machine Learning Models (Against Detectors/Generative odels/RL) Evasion Attacks Against Machine Learning Models (Blackbox Attacks) Detection Against Adversarial Attacks Defenses Against Adversarial Attacks (Empirical) Defenses Against Adversarial Attacks (Theoretic) Poisoning Attacks Against Machine Learning Models