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<p align=center> <img src="https://github.com/lishenghui/blades/blob/master/docs/source/images/client_pipeline.png" width="1000" alt="Blades Logo"> </p>

Installation

.. code-block:: bash

git clone https://github.com/lishenghui/blades
cd blades
pip install -v -e .
# "-v" means verbose, or more output
# "-e" means installing a project in editable mode,
# thus any local modifications made to the code will take effect without reinstallation.

.. code-block:: bash

cd blades/blades
python train.py file ./tuned_examples/fedsgd_cnn_fashion_mnist.yaml

Blades internally calls ray.tune <https://docs.ray.io/en/latest/tune/tutorials/tune-output.html>_; therefore, the experimental results are output to its default directory: ~/ray_results.

Experiment Results

.. image:: https://github.com/lishenghui/blades/blob/master/docs/source/images/fashion_mnist.png

.. image:: https://github.com/lishenghui/blades/blob/master/docs/source/images/cifar10.png

Cluster Deployment

To run blades on a cluster, you only need to deploy Ray cluster according to the official guide <https://docs.ray.io/en/latest/cluster/user-guide.html>_.

Built-in Implementations

In detail, the following strategies are currently implemented:

Attacks

General Attacks ^^^^^^^^^^^^^^^^^ +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+ | Strategy | Description | Sourse | +====================+==========================================================================================================================================================================================================+===========================================================================================================+ | Noise | Put random noise to the updates. | Sourse <https://github.com/lishenghui/blades/blob/master/blades/adversaries/noise_adversary.py>_ | +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+ | Labelflipping | Fang et al. Local Model Poisoning Attacks to Byzantine-Robust Federated Learning <https://www.usenix.org/conference/usenixsecurity20/presentation/fang>, USENIX Security' 20 | Sourse <https://github.com/lishenghui/blades/blob/master/blades/adversaries/labelflip_adversary.py> | +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+ | Signflipping | Li et al. RSA: Byzantine-Robust Stochastic Aggregation Methods for Distributed Learning from Heterogeneous Datasets <https://ojs.aaai.org/index.php/AAAI/article/view/3968>, AAAI' 19 | Sourse <https://github.com/lishenghui/blades/blob/master/blades/adversaries/signflip_adversary.py> | +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+ | ALIE | Baruch et al. A little is enough: Circumventing defenses for distributed learning <https://proceedings.neurips.cc/paper/2019/hash/ec1c59141046cd1866bbbcdfb6ae31d4-Abstract.html>_ NeurIPS' 19 | Sourse <https://github.com/lishenghui/blades/blob/master/blades/adversaries/alie_adversary.py>_ | +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+ | IPM | Xie et al. Fall of empires: Breaking byzantine- tolerant sgd by inner product manipulation <https://arxiv.org/abs/1903.03936>, UAI' 20 | Sourse <https://github.com/lishenghui/blades/blob/master/blades/adversaries/ipm_adversary.py> | +--------------------+----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------+

Adaptive Attacks ^^^^^^^^^^^^^^^^^ +--------------------------+-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+-----------------------------------------------------------------------------------------------------------------+ | Strategy | Description | Sourse | +==========================+=====================================================================================================================================================================================+================================================================