Code corresponding to the paper "Adversarial Examples are not Easily Detected..."
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README

This repository contains the code for the paper "Adversarial Examples
Are Not Easily Detected: Bypassing Ten Detection Methods".

This code is very much "research code": it will reproduce all of the
results in the paper, but may require some tweaking to do so. I would
not recommend building on top of this code; it is provided as a
reference of exact details of the experiments and attacks. The attacks
performed are only designed to bypass these specific defenses, and
will probably not work on other defenses. Properly evaluating a new
defense will require performing this type of evaluation on that other
defense, not just applying these attacks to a new defense.

To make this code works will require also cloning the repository at
https://github.com/carlini/nn_robust_attacks to make the adversarial
examples.

Some difficulties to be aware of:
 - there are some dependencies between files (e.g., some file generate
   outputs that other files use).
 - some of the files contain the code for multiple experiments (e.g.,
   both the standard and black-box attack) and one of these two will
   be commented out.
 - some files are set up to run more quickly (e.g., by training a
   resnet for only 20 epochs) for simple tests and should be changed
   to a larger number to achieve a proper analysis.
 - a few of the experiments are finiky (e.g., training the layer
   detector and CIFAR outlier class detector will need hyperparameter
   search to do well, otherwise it won't find a good model). However,
   if this search is not done completely, the results should only be
   stronger than the paper results (I tried my best to find the best
   possible defense parameters + random initialization).


This code is provided under the BSD 2-Clause, Copyright 2017 to
Nicholas Carlini.