A pytorch implementation of "Towards Evaluating the Robustness of Neural Networks"

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'.

• python==3.6
• numpy==1.14.2
• pytorch==1.0.1

• 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.

• This Repository won't be updated.
• Please check the package of adversarial attacks in pytorch