This is the implement of the papaer titled "MetaFinger: Fingerprinting the Deep Neural Networks with Meta-training" on IJCAI22

Run the Code

0. Requirements

The code was tested using Pytorch 1.8.0, python 3.7.

1. Prepare the models

You can train your models according to the paper or download the models form Google Driver, then put them under the main folder.

2. Generate the query set

meta_learning.py is the main file to generate the query set.

python meta_learning.py

3. Eval the query set

input_trans.py obtains the query set accuracy under various input modification operations like image blur or noising. eval_model.py evaluates the query set accuracy under various model modifications such as fine-tuning and weight pruning.