Hacking Machine Learning

Learn how to poison, backdoor and steal machine learning models in this course.

4 videos  //  13 minutes of training

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Course description

This course will teach you some of the darker, less publicized attacks on machine learning. You will learn how to steal machine learning models (i.e., create high-fidelity copies of black-box machine learning models), how to poison ML models so that their performance is degraded, and how to perform backdoor attacks on ML. The lessons in this course will be solidified through an assignment on backdoor attacks on ML.

Course syllabus

Model-Stealing Attacks on Machine LearningDuration: 6:07

Machine Learning PoisoningDuration: 4:59

Backdoor Attacks on Machine LearningDuration: 2:22

Assignment - Backdoor Attacks on Machine LearningDuration: 0:00

Meet the author

Emmanuel Tsukerman

LinkedIn

Dr. Tsukerman graduated from Stanford University and UC Berkeley. In 2017, his machine-learning-based anti-ransomware product won Top 10 Ransomware Products by PC Magazine. In 2018, he designed a machine-learning-based malware detection system for Palo Alto Network's WildFire service (over 30,000 customers). In 2019, Dr. Tsukerman authored the Machine Learning for Cybersecurity Cookbook and launched the Infosec Skills Cybersecurity Data Science Learning Path.

Plans & pricing

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  • 190+ role-guided learning paths (e.g., Ethical Hacking, Threat Hunting)
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  • 190+ role-guided learning paths and assessments (e.g., Incident Response)
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