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Explore the critical security challenges in Machine Learning (ML) lifecycle and learn effective strategies to mitigate them in this insightful conference talk by Alejandro Saucedo, Chief Scientist at the Institute for Ethical AI & Machine Learning. Delve into the concept of MLSecOps and its importance in securing large-scale production ML systems. Gain valuable knowledge on various security areas within MLOps phases, including explainability, GPU acceleration, and privacy-preserving ML. Discover the OWASP Top 10 for Machine Learning and access additional resources to enhance your understanding of ML security. This comprehensive presentation offers essential insights for professionals working with ML systems in critical use cases, emphasizing the paramount importance of securing MLOps infrastructure.
Syllabus
- Introductions
- About Alejandro Saucedo
- Security Challenges in Machine Learning
- What is MLSecOps
- TLDR; Machine Learning Deployed
- Security Areas in Phases of MLOps
- OWASP Top 10 For Machine Learn
- Resources for Talk
Taught by
Open Data Science