伊利诺伊大学厄巴纳-香槟分校(University of Illinois at Urbana-Champaign,缩写为UIUC),创建于1867年,位于伊利诺伊州幽静的双子城厄巴纳–香槟市,是一所世界著名的公立研究型大学。 [1] 该校是美国“十大联盟(Big Ten)”创始成员,美国大学协会(AAU)成员,被誉为“公立常春藤”,与加州大学伯克利分校及密歇根大学安娜堡分校并称“美国公立大学三巨头”。

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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

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