Table 3 Classification accuracy on the MNIST test dataset under the white-box attack
From: Secure machine learning against adversarial samples at test time
| Attack | FGSM | C&W | BIM | DeepFool |
|---|---|---|---|---|
| Original | 29% | 7% | 7% | 29% |
| Adversarial training (ART) | 98% | 49% | 98% | 42% |
| Robust classifier | 100% | 98% | 99% | 99% |