FLEX-Clash

flex-clash is a Python library dedicated to adversarial attacks and defences in Federated Learning. It offers the state-of-the methods and features to ease the implementation of custom methods. It is intended to extend the FLEXible framework.

Details

This repository includes both:

• Features to implement poisoning attacks in Federated Learning.
• Features to implement defences in the aggregator in Federated Learning.
• State-of-the-art defences implementedin FLEXible.

Folder structure

• flexclash/data: which contains the features to poison the clients' data.
• flexclash/model: which contains the features to poison the clients' model updates.
• flexclash/pool: which contains the features to implement any defence in the aggregation operator as well as the state-of-the-art implemented defences.
• notebooks: which contains explanatory notebooks showing how to implement poisoning attacks and use the implemented defences.
• test: which contains the test for the implemented features.

Explanatory notebooks

• Poisoning_data_FLEX.ipynb: A notebook showing how to implement data-poisoning attacks using flexclash including both byzantine and backdoor attacks.
• Poisoning_model_FLEX.ipynb: A notebook showing how to implement model-poisoning attacks using flexclash.
• Defences_FLEX.ipynb: A notebook showing how to employ defences against adversarial attacks using flexclash.

Features

In the following we detail the poisoning attacks implemented:

In the following we detail the defences implemented:

Installation

In order to install this repo locally:

pip install -e .

FLEX-Clash is available on the PyPi repository and can be easily installed using pip:

pip install flex-clash

Citation

If you use this repository in your research work, please cite Flexible paper: