/deepxplore

DeepXplore code release

Primary LanguagePython

DeepXplore: Systematic DNN testing (SOSP'17)

See the SOSP'17 paper DeepXplore: Automated Whitebox Testing of Deep Learning Systems for more details.

Prerequisite

Python

The code should be run using python 2.7.12, Tensorflow 1.3.0, and Keras 2.0.8.

Tensorflow

sudo pip install tensorflow

if you have gpu,

sudo pip install tensorflow-gpu

Keras

sudo pip install keras

Mimicus

Install from here.

File structure

  • MNIST - MNIST dataset.
  • ImageNet - ImageNet dataset.
  • Driving - Udacity self-driving car dataset.
  • PDF - Benign/malicious PDFs captured from VirusTotal/Contagio/Google provided by Mimicus.
  • Drebin - Drebin Android malware dataset.

To run

In every directory

python gen_diff.py

Note

The trained weights are provided in each directory (if required). Drebin's weights are not part of this repo as they are too large to be hosted on GitHub. Download from here and put them in ./Drebin/.

Coming soon

How to test your own DNN models.