Research Article
PBDT: Python Backdoor Detection Model Based on Combined Features
Table 6
Performance comparison of different feature combinations.
| | Features | Accuracy | Precision | Recall (TPR) | TNR | F1-score |
| #1 | Call | 0.9342 | 0.8805 | 0.8696 | 0.9575 | 0.8750 | #2 | Text | 0.9391 | 0.9026 | 0.8634 | 0.9664 | 0.8825 | #3 | Opcode | 0.9441 | 0.8757 | 0.9193 | 0.9530 | 0.8970 |
| | #1+#2 | 0.9589 | 0.9146 | 0.9317 | 0.9687 | 0.9231 | | #1+#3 | 0.9638 | 0.9264 | 0.9379 | 0.9732 | 0.9321 | | #2+#3 | 0.9473 | 0.8817 | 0.9255 | 0.9553 | 0.9030 |
| PBDT | #1+#2+#3 | 0.9770 | 0.9623 | 0.9503 | 0.9866 | 0.9563 |
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