This repo has an implemntation for our paper GenAttack: Practical Black-box Attacks with Gradient-Free Optimization
Download Inception-v3
model checkpoint
python setup_inception.py
Run attack without dimensionality reduction and adaptive parameter scaling
python main.py --input_dir=./images/ --test_size=1 \
--eps=0.05 --alpha=0.15 --mutation_rate=0.005 \
--max_steps=500000 --output_dir=attack_outputs \
--pop_size=6 --target=704 --adaptive=False
Original class: Squirrl, Adversarial class: Parking Meter, Number of queries=74,171
For more query efficiency
Run attack with dimensionality reduction and adaptive parameter scaling
python main.py --input_dir=./images/ --test_size=1 \
--eps=0.05 --alpha=0.15 --mutation_rate=0.10 \
--max_steps=100000 --output_dir=attack_outputs \
--pop_size=6 --target=704 --adaptive=True --resize_dim=96
Original class: Squirrl, Adversarial class: Parking Meter, Number of queries=11,696
More options:
- If you want to test on a single image, add the FLAG:
--test_example=xx
. - To specify a target class, instead of using a random target, add the flag
--target=xx
.
- This project is maintained by: Moustafa Alzantot (malzantot)