Fighting Gradients with Gradients: Dynamic Defenses against Adversarial Attacks

Dequan Wang, An Ju, Evan Shelhamer +2

Adversarial attacks optimize against models to defeat defenses. Existing defenses are static, and stay the same once trained, even while attacks change. We argue that models should…