Pytorch Implementation of FedDefender: Client-Side Attack-Tolerant Federated Learning
- Unique client-side defense strategy, FedDefender, that can train robust local models against malicious attacks from adversaries
- Designing an attack-tolerant local meta update that helps discover noise-tolerant parameters for local models by utilizing a synthetically corrupted training set
- Introducing an attack-tolerant global knowledge distillation technique that efficiently aligns the local model’s knowledge to the global data distribution while reducing the negative effects of false information in the possibly-corrupted global model
- torch==1.9.0
- torchvision==0.10.0
- scikit-learn==0.24.2
- scipy==1.3.0
- numpy==1.19.2
usage: main.py [-h] [--model MODEL] [--dataset DATASET] [--net_config NET_CONFIG] [--partition PARTITION] [--batch-size BATCH_SIZE] [--lr LR] [--epochs EPOCHS] [--n_parties N_PARTIES] [--n_parties_per_round N_PARTIES_PER_ROUND] [--alg ALG] [--comm_round COMM_ROUND] [--init_seed INIT_SEED] [--dropout_p DROPOUT_P] [--datadir DATADIR] [--reg REG] [--logdir LOGDIR] [--modeldir MODELDIR] [--beta BETA] [--device DEVICE] [--log_file_name LOG_FILE_NAME] [--optimizer OPTIMIZER] [--temperature TEMPERATURE] [--attacker_type ATTACKER_TYPE] [--attacker_ratio ATTACKER_RATIO] [--noise_ratio NOISE_RATIO] [--global_defense GLOBAL_DEFENSE] Parser optional arguments: -h, --help show this help message and exit --model MODEL neural network used in training --dataset DATASET dataset used for training --net_config NET_CONFIG --partition PARTITION the data partitioning strategy --batch-size BATCH_SIZE input batch size for training --lr LR learning rate --epochs EPOCHS number of local epochs --n_parties N_PARTIES number of workers in a distributed cluster --n_parties_per_round N_PARTIES_PER_ROUND number of workers in a distributed cluster per round --alg ALG training strategy: defender/vanilla --comm_round COMM_ROUND number of maximum communication roun --init_seed INIT_SEED Random seed --dropout_p DROPOUT_P Dropout probability. --datadir DATADIR Data directory --reg REG L2 regularization strength --logdir LOGDIR Log directory path --modeldir MODELDIR Model directory path --beta BETA The parameter for the dirichlet distribution for data partitioning --device DEVICE The device to run the program --log_file_name LOG_FILE_NAME The log file name --optimizer OPTIMIZER the optimizer --temperature TEMPERATURE the temperature parameter for knowledge distillation --attacker_type ATTACKER_TYPE attacker type (either untargeted or untargeted_diverse) --attacker_ratio ATTACKER_RATIO ratio for number of attackers --noise_ratio NOISE_RATIO noise ratio for label flipping (0 to 1) --global_defense GLOBAL_DEFENSE communication strategy: average/median/krum/norm/residual