This repository contains code for the paper Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models (S&P'22).
The code is run successfully using Python 3.6.10 and Tensorflow 2.2.0.
We recommend using conda to install the tensorflow-gpu environment:
$ conda create -n tf2-gpu tensorflow-gpu==2.2.0
$ conda activate tf2-gpu
To run code in the jupyter notebook, you should add the kernel:
$ pip install ipykernel
$ python -m ipykernel install --name tf2-gpu
DeepJudge
: model similarity metrics and test case generation methods.train_models
: train clean models and suspect models.watermarking-whitebox
: a TF2 implementation of [1]. (Keras version)watermarking-blackbox
: a TF2 implementation of [2].fingerprinting-blackbox
: a TF2 implementation of [3].
Reference:
[1] Uchida et al. "Embedding watermarks into deep neural networks." ICMR 2017.
[2] Zhang et al. "Protecting intellectual property of deep neural networks with watermarking." AisaCCS 2018.
[3] Cao et al. "IPGuard: Protecting intellectual property of deep neural networks via fingerprinting the classification boundary." AsiaCCS 2021.
See the README.md
in each directory.