pyproject.toml

[build-system]
requires = ["hatchling"]
build-backend = "hatchling.build"

[project]
name = "bft-federated-learning"
version = "1.0.0"
description = "Federated Learning with Byzantine Fault Tolerance (BFT)"
license = "Apache-2.0"
dependencies = [
    "flwr[simulation]>=1.12.0",
    "flwr-datasets[vision]>=0.3.0",
    "torch==2.2.1",
    "torchvision==0.17.1",
    "wandb==0.18.7",
    "matplotlib",
    "numpy",
    "pandas",
    "scipy",
]

[tool.hatch.build.targets.wheel]
packages = ["."]

[tool.flwr.app]
publisher = "muticia"

[tool.flwr.app.components]
serverapp = "app.server_app:app"
clientapp = "app.client_app:app"

[tool.flwr.federations]
default = "local-simulation"

[tool.flwr.app.config]
num-server-rounds = 20
fraction-fit = 1.0
local-epochs = 3
batch-size = 32
pretrained-model-path = "results/model/cifar10_cnn_model_weights.pth"

# BFT Strategy Configuration
strategy-type = "fedavg"  # fedavg, krum, trimmed_mean
byzantine-clients = 0
randomize-byzantine-strategy = false
byzantine-attack-strategy = "zero_update"  # sign_flip, gaussian_noise, constant_bias, zero_update
byzantine-attack-intensity = 1.0  # 0.1, 0.5, 1.0 (10 for constant_value)

[tool.flwr.federations.local-simulation]
options.num-supernodes = 100
options.seed = 42