Intrusion Detection on NF-BoT-IoT
96.43AccuracyGraphSAGE
Evaluation results
| Method | Links | |||||||
|---|---|---|---|---|---|---|---|---|
| GraphSAGE2026.03 | 96.43 | 91.67 | 97.83 | 94.34 | 4.35 | 0 | 95.65 | |
| ClusterGCN2026.03 | 92.86 | 85.71 | 95.65 | 89.39 | 8.7 | 0 | 91.3 | |
| TransformerConv2026.03 | 92.86 | 85.71 | 95.65 | 89.39 | 8.7 | 0 | 91.3 | |
| Q-AGNN2026.03 | 89.29 | 81.06 | 85.65 | 83.03 | 8.7 | 20 | 91.3 | |
| GCN2026.03 | 89.29 | 81.06 | 85.65 | 83.03 | 8.7 | 20 | 91.3 | |
| SuperGAT2026.03 | 89.29 | 83.33 | 77.83 | 80.14 | 4.35 | 40 | 95.65 | |
| GAT2026.03 | 78.57 | 40.74 | 47.83 | 44 | 4.35 | 100 | 95.65 | |
| GINConv2026.03 | 75 | 70.83 | 84.78 | 70.44 | 30.43 | 0 | 69.57 |