Table 4. Validation results (%) of comparison with machine learning and deep learning model on malware detection.
| Approach | F1-score | Precision | Recall | Accuracy |
|---|---|---|---|---|
| Naive Bayes | 65.96 | 67.69 | 70.90 | 67.08 |
| Decision tree | 89.47 | 91.86 | 87.78 | 91.51 |
| Logistic regression | 85.59 | 84.72 | 86.77 | 87.45 |
| SVM | 85.88 | 84.69 | 87.82 | 87.48 |
| TextCNN | 96.09 | 95.58 | 96.63 | 96.63 |
| RNN | 87.05 | 87.11 | 87.00 | 89.00 |
| Attention_BILSTM | 90.22 | 92.34 | 88.68 | 92.03 |
| Proposed method | 98.59 | 98.37 | 98.82 | 98.78 |