Hacking Machine Learning Course

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

1 hour, 14 minutes

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.

Syllabus

Backdoor Attacks on Machine Learning

File - 01:00:00
Backdoor Attacks on Machine Learning

Video - 00:01:00
Backdoor Attacks on Machine Learning Assignment

Video - 00:02:00
Machine Learning Poisoning

Video - 00:05:00
Model-Stealing Attacks on Machine Learning

Video - 00:06:00

Meet the author

Emmanuel Tsukerman

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.

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Associated NICE Work Roles

All Infosec training maps directly to the NICE Workforce Framework for Cybersecurity to guide you from beginner to expert across 52 Work Roles.

  • Law Enforcement / Counterintelligence Forensics Analyst
  • Cyber Defense Forensics Analyst
  • Data Analyst

Plans & pricing

Infosec Skills Personal

$299 / year

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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)
  • 100s of hands-on labs in cloud-hosted cyber ranges
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  • Custom certification practice exams (e.g., CISSP, CISA)
  • Optional upgrade: Guarantee team certification with live boot camps

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