This repo contains an ipython notebook (along with corresponding helper python classes) that implements adversarial example generation for a neural network trained on MNIST, and also implements some (very) simple security measures against adversarial attacks. The majority of the base neural network impelmentation was shamelessly lifted from neuralnetworksanddeeplearning.com. To run this notebook you will have to have jupyter notebook or ipython notebook installed. In addition, the code will need numpy and matplotlib as dependencies.

Once everything is installed go to the root directory of this repo in the terminal and run either

$ jupyter notebook

or

$ ipython notebook

A window should open up automatically in your browser. If not the output to the terminal should have a link you can put into a browser of your choice. It looks something like this

http://localhost:8888/?token=e848ccafeeea4a0d9d78659f943eedd4e94414add29f2f82

Finally, in the tree view of the ipython notebook click on adversarial_example.ipynb to start the notebook.

For more info about how to use Jupyter Notebooks check out the docs