Code to Fingerprint any model with Benign Inputs
Due to the lack of space, only Top-1 data is released in the GitHub.
Some results of our paper need images. We provide a small set of 1000 images. These images are the ones with the highest entroyp score.
First, install requirements
pip install -r requirements
python known_detection.py --input ./data/predictions --score mean_case --family pure --max_drop -0.15
family argument can be choosen between: pure, variation, singleton
python known_identification.py --input ./data/predictions --score mean_case --family pure --max_drop -0.15
family argument can be choosen between: pure, variation, singleton
python unknown_detection.py --input ./data/predictions/ --output_dir ./results/ --delegate close --family pure --n_images 10 50 100 150 200
python unknown_detection.py --input ./data/predictions/ --output_dir ./results/ --delegate close --family pure --n_images 10 50 100 150 200
python unknown_identification_variation.py --input ./data/predictions/ --output_dir ./results/ --delegate middle close --n_images 50 100 200 --sort_images entropy --n_gen 20