Research Article
Malware Detection on Byte Streams of PDF Files Using Convolutional Neural Networks
Table 3
Experimental results with the PDF dataset, where the two values of each cell are of ‘benign’ and ‘malicious’, respectively.
| Model | Precision | Recall | F1 |
| DT | 96.00 / 90.30 | 89.70 / 96.30 | 92.70 / 93.20 | NB | 88.40 / 99.70 | 99.70 / 87.00 | 93.70 / 92.90 | SVM | 94.70 / 98.90 | 99.00 / 94.40 | 96.80 / 96.60 | RF | 93.50 / 99.40 | 99.40 / 93.10 | 96.40 / 96.10 |
| Emb+Conv+Conv+Pool+FC | 99.76 / 100.0 | 97.37 / 97.37 | 98.48 / 98.65 | Conv+Conv+Pool+FC | 99.78 / 100.0 | 92.62 / 97.27 | 95.71 / 98.61 | Emb+Conv+Pool+FC | 99.73 / 100.0 | 94.94 / 97.78 | 97.12 / 98.87 | Emb+Conv+Conv+FC | 99.67 / 100.0 | 97.78 / 92.32 | 98.55 / 96.00 | Emb+Conv+Conv+Conv+Pool+FC | 99.70 / 100.0 | 92.21 / 95.35 | 95.36 / 97.60 |
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