Evaluate the impact of privacy issues, cyberattacks, and malware on your AI application : Testing Practical Defense from

The video tutorial discusses defense-enhanced models, focusing on adversarial training to improve model robustness. It covers Natural Adversarial Training (NAT) and Ensemble Adversarial Defense (ET), highlighting their implementation and results. The tutorial also explains how to evaluate these defenses using specific metrics, ensuring the new models maintain accuracy while being more resistant to attacks.

Describe the ensemble adversarial defense approach.

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What parameters should be monitored when comparing defenses?

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