Table 9.
Detection Comparison of proposed methods with existing methods on Dataset 3.
| Phishing Models | Accuracy (%) | F-Measure | AUC | TP-Rate | FP-Rate | MCC |
|---|---|---|---|---|---|---|
| Rahman, et al. [34] (KNN) | 88.00 | - | - | - | 0.099 | - |
| Rahman, et al. [34] (SVM) | 87.00 | - | - | - | 0.087 | - |
| ∗RoF-FT-1 | 89.87 | 0.899 | 0.973 | 0.899 | 0.071 | 0.824 |
| ∗RoF-FT-2 | 91.06 | 0.911 | 0.977 | 0.911 | 0.065 | 0.842 |
| ∗RoF-FT-3 | 89.80 | 0.898 | 0.954 | 0.898 | 0.070 | 0.825 |
| ∗BG-FT-1 | 88.77 | 0.888 | 0.972 | 0.888 | 0.079 | 0.808 |
| ∗BG-FT-2 | 90.32 | 0.903 | 0.978 | 0.903 | 0.073 | 0.828 |
| ∗BG-FT-3 | 88.70 | 0.887 | 0.962 | 0.887 | 0.076 | 0.810 |
| ∗BT-FT-1 | 89.06 | 0.891 | 0.963 | 0.891 | 0.082 | 0.808 |
| ∗BT-FT-2 | 89.28 | 0.893 | 0.967 | 0.893 | 0.079 | 0.812 |
| ∗BT-FT-3 | 87.73 | 0.877 | 0.966 | 0.877 | 0.091 | 0.785 |
∗
Indicates methods proposed in this study.