Gradient-based label leakage attacks recover activity class labels from federated HAR updates with high accuracy, especially under sequential sampling, and standard local privacy defenses provide only partial protection.
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Label Leakage in Federated Inertial-based Human Activity Recognition
Gradient-based label leakage attacks recover activity class labels from federated HAR updates with high accuracy, especially under sequential sampling, and standard local privacy defenses provide only partial protection.