Skip to content

MadryLab/blackbox-bandits

master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
src
 
 
 
 
 
 
 
 

Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors

This is the code for reproducing the paper "Prior Convictions: Black-box Adversarial Attacks with Bandits and Priors" (arxiv) to appear at ICLR 2019. The paper can be cited as follows:

@article{IEM2018PriorCB,
  title={Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors},
  author={Andrew Ilyas and Logan Engstrom and Aleksander Madry},
  journal={ICLR 2019},
  year={2018},
  url={https://arxiv.org/abs/1807.07978}
}

Results

Avg Queries Failure Rate Avg Queries on NES success
Method l-inf l-2 l-inf l-2 l-inf l-2
NES 1735 2938 22.2% 34.4% 1735 2938
Bandits[T] (ours) 1781 2690 11.6% 30.4% 1214 2421
Bandits[TD] (ours) 1117 1858 4.6% 15.5% 703 999

Reproducing the results

Requirements

  • Pytorch (torch, torchvision) packages
  • argparse package

The results can be reproduced (with the default hyperparameters) with the following command:

python main.py [--nes] [--tiling] --json-config [configs/l2.json | configs/linf.json | configs/linf-nes.json | configs/l2-nes.json]

You can run python main.py --help to see all of the available options/hyperparameters. Although the hyperparameters were tuned for Inception-v3, the attack can by run with the flag --classifier {inception_v3,resnet50,vgg16_bn} to attack other classifiers.

About

Code for "Prior Convictions: Black-Box Adversarial Attacks with Bandits and Priors"

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages