from .prototype import NormalCase
[docs]class BadNet(NormalCase):
r"""Badnets: Identifying vulnerabilities in the machine learning model supply chain.
basic structure:
1. config args, save_path, fix random seed
2. set the clean train data and clean test data
3. set the attack img transform and label transform
4. set the backdoor attack data and backdoor test data
5. set the device, model, criterion, optimizer, training schedule.
6. attack or use the model to do finetune with 5% clean data
7. save the attack result for defense
.. code-block:: python
attack = BadNet()
attack.attack()
.. Note::
@article{gu2017badnets,
title={Badnets: Identifying vulnerabilities in the machine learning model supply chain},
author={Gu, Tianyu and Dolan-Gavitt, Brendan and Garg, Siddharth},
journal={arXiv preprint arXiv:1708.06733},
year={2017}}
Args:
attack (string): name of attack, use to match the transform and set the saving prefix of path.
attack_target (Int): target class No. in all2one attack
attack_label_trans (str): which type of label modification in backdoor attack
pratio (float): the poison rate
bd_yaml_path (string): path for yaml file provide additional default attributes
patch_mask_path (string): path for patch mask
**kwargs (optional): Additional attributes.
"""