Graph Multiple Sensitive Attribute Inference Attack on German
72.62AATaipan
Evaluation results
| Method | Links | ||||||||
|---|---|---|---|---|---|---|---|---|---|
| TaipanEncoder=GraphSAGE2026.02 | 72.62 | 77.11 | 16.99 | 41.41 | 16.33 | 60 | 3.38 | 64.4 | |
| TaipanEncoder=GCN2026.02 | 70.01 | 76.1 | 7.58 | 31.44 | 21.33 | 57 | 9.88 | 46.35 | |
| SingP.Encoder=GraphSAGE2026.02 | 69.47 | 54.72 | 8.28 | 55.69 | 35.2 | 35.2 | -1.8 | 32.43 | |
| PreTr.Encoder=GraphSAGE2026.02 | 69.37 | 70.49 | 19.95 | 53.75 | 19.67 | 53 | 6.26 | 56.15 | |
| TaipanEncoder=GIN2026.02 | 67.3 | 72.28 | 5.7 | 28.12 | 30.67 | 39 | 18.91 | 62.58 | |
| SingP.Encoder=GCN2026.02 | 66.5 | 42.5 | 13.46 | 88.05 | 33.27 | 14 | 0.48 | 34.36 | |
| PreTr.Encoder=GIN2026.02 | 66.39 | 73.38 | 21.16 | 33.26 | 25 | 49 | 9.39 | 57.2 | |
| PreTr.Encoder=GCN2026.02 | 66.34 | 73.62 | 10.45 | 40.24 | 20.33 | 54 | 7.22 | 42.77 | |
| SingP.Encoder=GIN2026.02 | 55.64 | 31.49 | 22.18 | 89.5 | 34.8 | 12 | -8.37 | 6.89 | |
| TaipanGNN Backbone=GIN2026.02 | 54.28 | 70.91 | 1.25 | 9.46 | 42 | 34 | 43.01 | 13.97 | |
| Rand.Encoder=Real Value2026.02 | 54.21 | 60.25 | 13.08 | 58.7 | 36.33 | 26 | -2.28 | 20.37 | |
| TaipanGNN Backbone=GraphSAGE2026.02 | 51.93 | 66.3 | 2.96 | 3.57 | 44.5 | 33 | 35.42 | 29.36 | |
| SingP.GNN Backbone=GIN2026.02 | 51.66 | 78.44 | 4.69 | 15.27 | 34.7 | 46 | -10.37 | 4.08 | |
| TaipanGNN Backbone=GCN2026.02 | 50.75 | 74.22 | 1.51 | 34.16 | 32 | 44 | 31.37 | 5.88 | |
| SingP.GNN Backbone=GraphSAGE2026.02 | 50.74 | 71.06 | 3.28 | 34.37 | 35.5 | 38.6 | -8.62 | 5.9 | |
| PreTr.GNN Backbone=GraphSAGE2026.02 | 48.74 | 68.29 | 1.03 | 26.84 | 40.5 | 37 | 11.96 | 29.35 | |
| PreTr.GNN Backbone=GCN2026.02 | 47.2 | 75.34 | 5.6 | 31.93 | 34 | 40 | 45.62 | 23.15 | |
| PreTr.GNN Backbone=GIN2026.02 | 46.91 | 68.17 | 0.23 | 40.19 | 37.5 | 38 | 10.84 | 9.27 | |
| SingP.GNN Backbone=GCN2026.02 | 44.25 | 69.11 | 17.56 | 40.3 | 39.1 | 33 | 43.49 | 19.82 |