BadNets Backdoor Attack Robustness on Federated Learning Dataset
89.51AccuracyFLTrust
Evaluation results
| Method | Links | ||
|---|---|---|---|
| FLTrustModel=CNN2026.02 | 89.51 | 68.97 | |
| FedAVGModel=CNN2026.02 | 88.28 | 99.9 | |
| FlameModel=CNN2026.02 | 87.78 | 0.1 | |
| Multi-KrumModel=CNN2026.02 | 87.31 | 0.39 | |
| MedianModel=VGG192026.02 | 79.26 | 70.52 | |
| Trimmed-MeanModel=VGG192026.02 | 79.11 | 69.41 | |
| MedianModel=ResNet182026.02 | 78.91 | 66.13 | |
| FedAVGModel=VGG192026.02 | 78.89 | 74.69 | |
| Trimmed-MeanModel=ResNet182026.02 | 78.13 | 67.5 | |
| FedAVGModel=ResNet182026.02 | 77.58 | 70.53 | |
| FlameModel=ResNet182026.02 | 76.04 | 7.22 | |
| FLTrustModel=ResNet182026.02 | 75.72 | 75.84 | |
| FLTrustModel=VGG192026.02 | 75.1 | 67.3 | |
| Multi-KrumModel=ResNet182026.02 | 74.49 | 3.95 | |
| FlameModel=VGG192026.02 | 62.91 | 7.78 | |
| Multi-KrumModel=VGG192026.02 | 58.93 | 7.84 |