Table 8.
Detection Comparison of proposed methods with existing methods on Dataset 2.
| Phishing Models | Accuracy (%) | F-Measure | AUC | TP-Rate | FP-Rate | MCC |
|---|---|---|---|---|---|---|
| Chiew, et al. [12] | 94.60 | - | - | - | - | - |
| Rahman, et al. [34] (KNN) | 87.00 | - | - | - | 0.078 | - |
| Rahman, et al. [34] (SVM) | 91.00 | - | - | - | 0.067 | - |
| ∗RoF-FT-1 | 97.43 | 0.974 | 0.996 | 0.974 | 0.026 | 0.949 |
| ∗RoF-FT-2 | 98.32 | 0.983 | 0.998 | 0.983 | 0.017 | 0.966 |
| ∗RoF-FT-3 | 97.4 | 0.974 | 0.994 | 0.974 | 0.026 | 0.948 |
| ∗BG-FT-1 | 97.58 | 0.976 | 0.996 | 0.976 | 0.024 | 0.952 |
| ∗BG-FT-2 | 98.21 | 0.982 | 0.997 | 0.982 | 0.018 | 0.964 |
| ∗BG-FT-3 | 97.33 | 0.973 | 0.994 | 0.973 | 0.027 | 0.947 |
| ∗BT-FT-1 | 98.11 | 0.981 | 0.997 | 0.981 | 0.019 | 0.962 |
| ∗BT-FT-2 | 98.51 | 0.985 | 0.998 | 0.985 | 0.015 | 0.970 |
| ∗BT-FT-3 | 97.84 | 0.978 | 0.997 | 0.978 | 0.022 | 0.957 |
∗
Indicates methods proposed in this study.