reproduction of Thermometer Encoding: One Hot Way To Resist Adversarial Examples in pytorch
This is a repo trying to reproduce Thermometer Encoding: One Hot Way To Resist Adversarial Examples in pytorch.
I use ResNet-50 to reproduce the experiment instead of a Wide-ResNet. All LS-PGA attack is 7-step iterative white-box attack. However, I find that if I increase the attack step-size, attack failure rate will drop dramatically.
| clean | LS-PGA $$\xi=0.01$$ | LS-PGA $$\xi=0.1$$ | LS-PGA $$\xi=1$$ | results on the paper(LS-PGA) | results on the paper(clean) | |
|---|---|---|---|---|---|---|
| clean trained | 91.52% | 43.27% | 3.14% | 0.12% | 50.50% | 94.22% |
| adv trained | 89.75% | 74.00% | 27.44% | 15.02% | 79.16% | 89.88% |