Security Audits for Machine Learning Attacks

Explore the critical topic of security audits for machine learning attacks in this 42-minute conference talk from MLOps World: Machine Learning in Production. Gain insights from lead data scientists Navdeep Gill and Michelle Canco of H2O.AI as they delve into the vulnerabilities of ML models and the importance of implementing robust security measures. Learn about various known attacks that can compromise model outcomes or expose sensitive training data, and discover why traditional assessment methods fall short in detecting these threats. Understand the value of incorporating ML-specific attacks into existing white-hat hacking exercises and red-team audits. Acquire knowledge on common machine learning security attacks and practical remediation steps to safeguard your organization's ML systems. Enhance your understanding of responsible AI practices and strengthen your ability to protect against potential pitfalls in machine learning deployments.

Security Audits for Machine Learning Attacks