My federated learning project just showed that "high accuracy" can completely hide a model missing every single attack from an entire category, and I think more people should know about this [R]

So for context, I've been working on this research project comparing federated learning algorithms (FedAvg, FedProx, FedNova) against a centralized baseline for network intrusion detection, using the CICIDS2017 dataset split across four simulated "silos" by attack type. Three of the silos have tons