Table 7.
The performance of our model and others in the literature.
| Ref. | Dataset | Proposed Model | Acc | AUC | F1 | DR (TPR) | FA (FPR) | HD (TPR-FPR) |
|---|---|---|---|---|---|---|---|---|
| [34] | ISSDA | Clustering-based | - | - | - | 63.6 | 24.3 | - |
| [27] | ISSDA | MP-ANN | - | - | - | 93.4 | 1.9 | 91.5 |
| [29] | ISSDA | GRU RNN-based | - | - | - | 92.5 | 5 | 87.5 |
| [23] | ISSDA | SVM-based | - | - | - | 94 | 11 | 83 |
| [25] | ISSDA | Ensemble ML | - | 90 | - | - | - | - |
| [37] | ISSDA | SVM | 75.8 | 80.2 | - | - | - | - |
| [39] | ISSDA | DNN-based | - | - | - | 92.6 | 2.3 | 90.3 |
| [40] | ISSDA | Density-based clustering | 93.2 | 74.3 | 32.2 | - | - | - |
| [46] | ISSDA | Semi-supervised | - | 84.2 | 73.3 | - | - | - |
| [51] | ISSDA | Feedforward ANN based | 93.36 | - | - | 92.56 | 5.84 | 86.72 |
| Our work | ISSDA | CNN-based hybrid | 95.34 | 95.68 | 95.36 | 95.01 | 4.32 | 90.69 |