CW-pytorch
A pytorch implementation of "Towards Evaluating the Robustness of Neural Networks"
Summary
This code is a pytorch implementation of CW attack.
In this code, I used above methods to fool Inception v3.
'Giant Panda' used for an example.
You can add other pictures with a folder with the label name in the 'data/imagenet'.
Requirements
- python==3.6
- numpy==1.14.2
- pytorch==1.0.1
Important results not in the code
- This paper suggested new approach to the adversarial attack.(p.6-7)
- Compared 7 new objective functions(f) for generating adversarial images.
- Used tanh for solving box constraints.
- Three new attack algorithms proposed.(p.9-10)
- They are L_2, L_0, L_inf. (Among these, L_2 is implementd in this code)
- These attacks made the defensive distillation helpless.(p.12-14)
- All of new attack methods succeed with 100% success.
Notice
- This Repository won't be updated.
- Please check the package of adversarial attacks in pytorch