Model Hardening & Robustness

This lesson explores model hardening and robustness testing as critical components of AI security. Learners will examine how organizations strengthen machine learning models against adversarial attacks, manipulation attempts, unexpected inputs, and operational failures. The lesson covers adversarial machine learning, robustness evaluation, stress testing, red teaming, validation frameworks, and resilience engineering practices that help organizations improve the security, reliability, and trustworthiness of AI systems operating in real-world environments.