Table 13.
Combined performance results across UNSW-NB15 and CIC-IDS2017.
| Model | Dataset | Accuracy | Precision | Recall | F1-Score | Run |
|---|---|---|---|---|---|---|
| BERT | UNSW-NB15 | 0.9470 | 0.9481 | 0.9470 | 0.9473 | 4.5 |
| CIC-IDS2017 | 0.9500 | 0.9710 | 0.9500 | 0.9570 | 4.5 | |
| LSTM | UNSW-NB15 | 0.9097 | 0.9195 | 0.9097 | 0.9110 | 4.5 |
| CIC-IDS2017 | 0.9000 | 0.9640 | 0.9000 | 0.9210 | 4.5 | |
| Naïve Bayes | UNSW-NB15 | 0.6332 | 0.7550 | 0.6332 | 0.6306 | 4.5 |
| CIC-IDS2017 | 0.1380 | 0.9480 | 0.1380 | 0.1650 | 4.5 | |
| SVM | UNSW-NB15 | 0.8843 | 0.8848 | 0.8843 | 0.8845 | 4.5 |
| CIC-IDS2017 | 0.665 | 0.952 | 0.665 | 0.757 | 4.5 |