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Federated Learning Defense on N-BaIoT Label-Flipping Attack Scenario 1 (test)

97.41Accuracy

FedAvg

43.600457.570271.5485.5098Jan 10, 2026
Updated 4d ago

Evaluation Results

MethodLinks
2026.01
97.4197.351.85
2026.01
97.2196.127.2
2026.01
96.7195.870.72
2026.01
96.1396.123.45
2026.01
96.0296.455.12
2026.01
93.3191.6512.47
2026.01
91.5290.6712.97
2026.01
81.8581.4514.67
2026.01
73.8162.5162.1
2026.01
51.750100
2026.01
51.320100
2026.01
46.9562.91100
2026.01
46.9562.81100
2026.01
46.8962.65100
2026.01
45.9162.94100
2026.01
45.8562.1250.34
2026.01
45.8562.1250.34
2026.01
45.6762.1250.45