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FLIP: A Provable Defense Framework for Backdoor Mitigation in Federated Learning [ICLR‘23, Best Paper Award at ECCV’22 AROW Workshop]

Home Page: https://kaiyuanzhang.com

License: MIT License

Python 100.00%
backdoor backdoor-attacks backdoor-defense byzantine computer-vision defense distributed-computing federated-learning privacy python pytorch security

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flip's Issues

code doesn't work

AttributeError: module 'config' has no attribute 'AGGR_FOOLSGOLD'
I will be glad to see your code that is a completed version.

Ask for code help

Thank you for your article and code, which gave me a lot of help. I encountered difficulties during the experiment. I would like to ask if you can share with me the code to reproduce the previous defense method in the paper experiment, because my code I have limited abilities and can't do it myself, if you can help me, I will be very grateful!!

Code redundancy in the main.py file and aggregation model

In the main.py file, lines 167–194, what is the purpose of the phrase "logger.inflogger.info("end test the returned updates").
What I found in this code is that their local model doesn't change because each agent_name_key only contains one element.
Should we remove these lines of code, or is this my misunderstanding?

Anw, I thought FedAvg aggregation models would be based on one number of samples trained in each client, but in your code, the weight is equal for all clients, = self.params["lr_para"] / self.params["no_models"]. Could you explain this?

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