MagNet and "Efficient Defenses Against Adversarial Attacks" are Not Robust to Adversarial Examples

This is an incremental finding that highlights vulnerabilities in existing defenses for machine learning security, which is crucial for researchers and practitioners in adversarial robustness.

The paper tackles the problem of adversarial attacks on machine learning models by showing that two recently proposed defenses, MagNet and 'Efficient Defenses Against Adversarial Attacks', are not robust, as adversarial examples can be constructed to defeat them with only a slight increase in distortion.