This repository is an Pytorch implementation of paper: "SEAT: Similarity Encoder by Adversarial Training for Detecting Model Extraction Attack Queries".
Note: this is not the official implementation of SEAT, you can follow the paper here: https://dl.acm.org/doi/10.1145/3474369.3486863.
The code requires dependencies that can be installed using the pip environment file provided:
pip install -r requirements.txt
Run main.py to fine-tune encoder and then evaluate SEAT.
For CIFAR10
python3 main.py --arch vgg16_bn --task cifar10
Result preview for CIFAR10:
For MNIST
python3 main.py --arch lenet --task mnist
Download fine-tuned VGG encoder here: https://drive.google.com/drive/folders/1RgeDjPNs9Tswn7hmkzBLLSl8mRJxBFm4?usp=sharing
This library is under the MIT license. For the full copyright and license information, please view the LICENSE file that was distributed with this source code.