'''
This file is modified based on the following source:
link : https://github.com/RJ-T/NIPS2022_EP_BNP.
The defense method is called ep.
The update include:
1. data preprocess and dataset setting
2. model setting
3. args and config
4. save process
5. new standard: robust accuracy
6. reconstruct the layer norm for convnext and transformer
7. draw the corresponding images of asr and acc according to different proportions
basic sturcture for defense method:
1. basic setting: args
2. attack result(model, train data, test data)
3. ep defense:
a. calculate the entropy of each norm layer
b. prune the model depend on the mask
4. test the result and get ASR, ACC, RC
'''
from defense.base import defense
[docs]class ep(defense):
r"""Pre-activation Distributions Expose Backdoor Neurons
basic structure:
1. config args, save_path, fix random seed
2. load the backdoor attack data and backdoor test data
3. ep defense:
a. calculate the entropy of each norm layer
b. prune the model depend on the mask
4. test the result and get ASR, ACC, RC
.. code-block:: python
parser = argparse.ArgumentParser(description=sys.argv[0])
ep.add_arguments(parser)
args = parser.parse_args()
ep_method = ep(args)
if "result_file" not in args.__dict__:
args.result_file = 'one_epochs_debug_badnet_attack'
elif args.result_file is None:
args.result_file = 'one_epochs_debug_badnet_attack'
result = ep_method.defense(args.result_file)
.. Note::
@article{zheng2022pre,
title={Pre-activation Distributions Expose Backdoor Neurons},
author={Zheng, Runkai and Tang, Rongjun and Li, Jianze and Liu, Li},
journal={Advances in Neural Information Processing Systems},
volume={35},
pages={18667--18680},
year={2022}}
Args:
baisc args: in the base class
u (float): the u in the ep defense
u_min (float): the default minimum value of u
u_max (float): the default maximum value of u
u_num (float): the default number of u
Update:
All threshold evaluation results will be saved in the save_path folder as a picture, and the selected fixed threshold model results will be saved to defense_result.pt
"""