Research Article
Evaluation of Deep Learning Methods Efficiency for Malicious and Benign System Calls Classification on the AWSCTD
Table 3
Malware-type classification with the help of DL and SVM methods (AllMalware set).
| Count | Accuracy (percent) | Classification time (seconds) | LSTM | GRU | CNN | SVM | LSTM | GRU | CNN | SVM |
| 10 | 88.1 | 88.3 | 87.3 | 89.4 | 0.0000926 | 0.0000840 | 0.0000401 | 0.0000440 | 20 | 88.8 | 88.1 | 89.0 | 89.4 | 0.0001043 | 0.0000994 | 0.0000510 | 0.0000583 | 40 | 89.1 | 90.6 | 91.2 | 91.6 | 0.0001327 | 0.0001377 | 0.0000618 | 0.0000842 | 60 | 88.2 | 90.5 | 91.2 | 91.9 | 0.0001786 | 0.0001704 | 0.0000890 | 0.0000848 | 80 | 91.8 | 91.6 | 92.3 | 92.7 | 0.0002194 | 0.0002221 | 0.0001157 | 0.0000937 | 100 | 91.6 | 91.9 | 92.8 | 92.4 | 0.0002559 | 0.0002566 | 0.0001290 | 0.0001165 | 200 | 90.4 | 91.5 | 92.7 | 89.6 | 0.0004440 | 0.0004363 | 0.0003019 | 0.0002392 | 400 | 87.6 | 90.3 | 93.0 | 87.3 | 0.0009840 | 0.0008142 | 0.0006222 | 0.0006739 | 600 | 87.4 | 91.4 | 93.1 | 86.1 | 0.0023443 | 0.0023052 | 0.0016681 | 0.0015564 | 800 | 82.1 | 88.5 | 93.0 | 84.7 | 0.0043159 | 0.0037894 | 0.0023929 | 0.0022612 | 1000 | 75.5 | 89.6 | 93.1 | 83.2 | 0.0068075 | 0.0056159 | 0.0033276 | 0.0032245 |
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