Add Flower Baseline: FedDefender

[gautamjajoo]

Paper

Gill, Waris and Anwar, Ali and Gulzar, Muhammad Ali(2023) - FedDefender: Backdoor Attack Defense in Federated Learning

Link

https://arxiv.org/abs/2307.08672

Maybe give motivations about why the paper should be implemented as a baseline.

FedDefender is a defense against backdoor attacks in federated learning by leveraging differential testing for FL. FedDefender minimizes the impact of a malicious client on the global model by limiting its contribution to the aggregated global model. FedDefender fingerprints the neuron activations of clients’ models on the same input and uses differential testing to identify potential malicious clients.

Is there something else you want to add?

No response

Implementation

To implement this baseline, it is recommended to do the following items in that order:

For first time contributors

• Read the first contribution doc
• Complete the Flower tutorial
• Read the Flower Baselines docs to get an overview:
  • How to use Flower Baselines
  • How to contribute a Flower Baseline

Prepare - understand the scope

• Read the paper linked above
• Decide which experiments you'd like to reproduce. The more the better!
• Follow the steps outlined in Add a new Flower Baseline.
• You can use as reference other baselines that the community merged following those steps.

Verify your implementation

• Follow the steps indicated in the EXTENDED_README.md that was created in your baseline directory
• Ensure your code reproduces the results for the experiments you chose
• Ensure your README.md is ready to be run by someone that is no familiar with your code. Are all step-by-step instructions clear?
• Ensure running the formatting and typing tests for your baseline runs without errors.
• Clone your repo on a new directory, follow the guide on your own README.md and verify everything runs.