FS-TFP/tests/test_backdoor_attack.py

91 lines
3.0 KiB
Python

# Copyright (c) Alibaba, Inc. and its affiliates.
import unittest
from federatedscope.core.auxiliaries.data_builder import get_data
from federatedscope.core.auxiliaries.utils import setup_seed
from federatedscope.core.auxiliaries.logging import update_logger
from federatedscope.core.configs.config import global_cfg
from federatedscope.core.auxiliaries.runner_builder import get_runner
from federatedscope.core.auxiliaries.worker_builder import get_server_cls, get_client_cls
class Backdoor_Attack(unittest.TestCase):
def setUp(self):
print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
def set_config_femnist(self, cfg):
backup_cfg = cfg.clone()
import torch
cfg.use_gpu = torch.cuda.is_available()
cfg.device = 0
cfg.eval.freq = 1
cfg.eval.metrics = ['acc', 'correct', 'poison_attack_acc']
cfg.early_stop.patience = 0
cfg.federate.mode = 'standalone'
cfg.train.batch_or_epoch = 'epoch'
cfg.train.local_update_steps = 2
cfg.federate.total_round_num = 10
cfg.federate.sample_client_num = 20
cfg.federate.client_num = 200
cfg.data.root = 'test_data/'
cfg.data.type = 'femnist'
cfg.data.splits = [0.6, 0.2, 0.2]
cfg.data.batch_size = 32
cfg.data.subsample = 0.05
cfg.data.transform = [['ToTensor']]
cfg.model.type = 'convnet2'
cfg.model.hidden = 2048
cfg.model.out_channels = 62
cfg.train.optimizer.lr = 0.1
cfg.train.optimizer.weight_decay = 0.0
cfg.criterion.type = 'CrossEntropyLoss'
cfg.trainer.type = 'cvtrainer'
cfg.seed = 123
cfg.attack.attack_method = 'backdoor'
cfg.attack.attacker_id = -1
cfg.attack.inject_round = 0
cfg.attack.setting = 'fix'
cfg.attack.freq = 10
cfg.attack.label_type = 'dirty'
cfg.attack.trigger_type = 'gridTrigger'
cfg.attack.target_label_ind = 1
cfg.attack.mean = [0.9637]
cfg.attack.std = [0.1592]
return backup_cfg
def test_backdoor_edge_femnist_standalone(self):
init_cfg = global_cfg.clone()
backup_cfg = self.set_config_femnist(init_cfg)
setup_seed(init_cfg.seed)
update_logger(init_cfg)
data, modified_cfg = get_data(init_cfg.clone())
init_cfg.merge_from_other_cfg(modified_cfg)
self.assertIsNotNone(data)
Fed_runner = get_runner(data=data,
server_class=get_server_cls(init_cfg),
client_class=get_client_cls(init_cfg),
config=init_cfg.clone())
self.assertIsNotNone(Fed_runner)
test_best_results = Fed_runner.run()
print(test_best_results)
# TODO: use a resonable metric
self.assertGreater(
test_best_results["client_summarized_weighted_avg"]['test_acc'],
0.1)
init_cfg.merge_from_other_cfg(backup_cfg)
if __name__ == '__main__':
unittest.main()