S-O attack for TRADES

This is the code for Second Order attack (https://arxiv.org/pdf/1901.08573.pdf) for TRADE(https://arxiv.org/pdf/1901.08573.pdf). Currently we only have attacks on MNIST.

Prerequisites

• Python (3.6.4)
• Pytorch (0.4.1)
• CUDA
• numpy

Install

We suggest to install the dependencies using Anaconda or Miniconda. Here is an exemplary command:

$ wget https://repo.anaconda.com/archive/Anaconda3-5.1.0-Linux-x86_64.sh
$ bash Anaconda3-5.1.0-Linux-x86_64.sh
$ source ~/.bashrc
$ conda install pytorch=0.4.1

How to run the attack on MNIST?

• Step 1: Download mnist_X.npy and mnist_Y.npy.
• Step 2: Run pgd_attack_mnist_l2.py. The adversarial examples will be stored in data_attack/X_adv.npy.

In each iteration, it outputs the number of mis-classified examples in each batch and the largest L_2 norm of perturbations. Optionally, one can run data_attack/draw.py to see the images of the adversarial examples.