notesum.ai
Published at November 4Alignment-Based Adversarial Training (ABAT) for Improving the Robustness and Accuracy of EEG-Based BCIs
cs.HC
cs.AI
cs.LG
Released Date: November 4, 2024
Authors: Xiaoqing Chen, Ziwei Wang, Dongrui Wu

| Model | EA | Training | No | FGSM | FGSM | FGSM | PGD | PGD | PGD | AutoAttack | AutoAttack | AutoAttack | Avg. |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Attack | 0.01 | 0.03 | 0.05 | 0.01 | 0.03 | 0.05 | 0.01 | 0.03 | 0.05 | ||||
| EEGNet | w/o EA | BT | 60.78 | 36.14 | 8.89 | 1.66 | 35.92 | 7.70 | 1.05 | 35.64 | 7.32 | 0.94 | 19.60 |
| AT-FGSM 0.01 | 56.71 | 48.95 | 34.10 | 22.61 | 49.02 | 33.74 | 21.63 | 48.87 | 33.51 | 21.17 | 37.03 | ||
| AT-PGD 0.01 | 55.99 | 48.33 | 34.25 | 22.31 | 48.47 | 34.03 | 21.37 | 48.28 | 33.71 | 20.95 | 36.77 | ||
| with EA | BT | 69.79 | 57.54 | 35.11 | 19.98 | 57.50 | 34.74 | 19.01 | 57.46 | 34.49 | 18.45 | 40.41 | |
| ABAT-FGSM 0.01 | 71.08 | 64.11 | 49.52 | 35.65 | 64.12 | 49.28 | 35.11 | 64.08 | 49.10 | 34.70 | 51.67 | ||
| ABAT-FGSM 0.03 | 68.92 | 65.33 | 56.71 | 48.25 | 65.33 | 56.61 | 48.11 | 65.33 | 56.58 | 47.90 | 57.91 | ||
| ABAT-FGSM 0.05 | 65.46 | 62.91 | 57.29 | 51.34 | 62.92 | 57.23 | 51.35 | 62.91 | 57.20 | 51.16 | 57.98 | ||
| ABAT-PGD 0.01 | 73.28 | 66.82 | 51.53 | 37.49 | 66.80 | 51.29 | 36.70 | 66.78 | 51.09 | 36.34 | 53.81 | ||
| ABAT-PGD 0.03 | 70.69 | 66.85 | 58.81 | 49.76 | 66.85 | 58.83 | 49.50 | 66.85 | 58.74 | 49.31 | 59.62 | ||
| ABAT-PGD 0.05 | 67.48 | 64.75 | 59.26 | 53.16 | 64.75 | 59.25 | 53.15 | 64.74 | 59.19 | 53.00 | 59.87 | ||
| DeepCNN | w/o EA | BT | 54.06 | 31.61 | 6.93 | 1.02 | 31.29 | 6.30 | 0.82 | 31.08 | 5.97 | 0.68 | 16.98 |
| AT-FGSM 0.01 | 49.19 | 41.82 | 27.87 | 16.23 | 41.74 | 27.47 | 15.65 | 41.69 | 27.22 | 15.30 | 30.42 | ||
| AT-PGD 0.01 | 49.06 | 41.53 | 27.69 | 16.54 | 41.51 | 27.40 | 15.95 | 41.49 | 27.26 | 15.63 | 30.41 | ||
| with EA | BT | 59.70 | 44.21 | 20.41 | 7.70 | 43.98 | 19.43 | 6.42 | 43.84 | 18.88 | 5.93 | 27.05 | |
| ABAT-FGSM 0.01 | 62.73 | 53.20 | 35.08 | 21.58 | 53.15 | 34.57 | 20.78 | 53.15 | 34.32 | 20.37 | 38.89 | ||
| ABAT-FGSM 0.03 | 66.05 | 58.82 | 44.71 | 32.33 | 58.82 | 44.55 | 31.71 | 58.80 | 44.37 | 31.44 | 47.16 | ||
| ABAT-FGSM 0.05 | 63.88 | 59.08 | 48.74 | 38.71 | 59.08 | 48.66 | 38.49 | 59.08 | 48.60 | 38.28 | 50.26 | ||
| ABAT-PGD 0.01 | 61.54 | 52.28 | 34.23 | 21.14 | 52.20 | 33.77 | 20.22 | 52.17 | 33.56 | 19.88 | 38.10 | ||
| ABAT-PGD 0.03 | 64.98 | 58.64 | 44.82 | 32.72 | 58.60 | 44.68 | 32.19 | 58.59 | 44.60 | 31.88 | 47.17 | ||
| ABAT-PGD 0.05 | 62.83 | 58.00 | 48.01 | 38.25 | 58.00 | 47.92 | 37.96 | 57.97 | 47.81 | 37.80 | 49.45 | ||
| ShallowCNN | w/o EA | BT | 60.57 | 31.92 | 7.27 | 1.08 | 31.60 | 6.11 | 0.73 | 31.48 | 5.80 | 0.57 | 17.71 |
| AT-FGSM 0.01 | 57.47 | 47.15 | 29.57 | 16.87 | 47.13 | 29.37 | 16.00 | 47.08 | 29.05 | 15.46 | 33.51 | ||
| AT-PGD 0.01 | 57.47 | 47.49 | 29.73 | 16.80 | 47.48 | 29.64 | 16.06 | 47.44 | 29.24 | 15.44 | 33.68 | ||
| with EA | BT | 71.46 | 57.01 | 34.40 | 19.24 | 56.94 | 33.90 | 18.24 | 56.91 | 33.74 | 17.75 | 39.96 | |
| ABAT-FGSM 0.01 | 73.82 | 65.41 | 48.83 | 34.45 | 65.35 | 48.68 | 33.90 | 65.34 | 48.61 | 33.71 | 51.81 | ||
| ABAT-FGSM 0.03 | 74.79 | 68.58 | 54.99 | 42.48 | 68.57 | 54.85 | 42.21 | 68.56 | 54.81 | 42.08 | 57.19 | ||
| ABAT-FGSM 0.05 | 73.88 | 68.36 | 57.42 | 45.88 | 68.35 | 57.39 | 45.82 | 68.35 | 57.38 | 45.64 | 58.85 | ||
| ABAT-PGD 0.01 | 73.95 | 65.61 | 48.70 | 34.30 | 65.59 | 48.47 | 33.69 | 65.59 | 48.34 | 33.38 | 51.76 | ||
| ABAT-PGD 0.03 | 74.99 | 68.85 | 55.65 | 42.26 | 68.85 | 55.56 | 41.96 | 68.84 | 55.52 | 41.67 | 57.41 | ||
| ABAT-PGD 0.05 | 73.51 | 68.17 | 56.97 | 45.74 | 68.16 | 56.94 | 45.63 | 68.16 | 56.93 | 45.46 | 58.57 |