Research Article
LiDAR: A Light-Weight Deep Learning-Based Malware Classifier for Edge Devices
Table 6
The evaluation results on the Raspberry Pi using the three classifiers.
| Dataset | Classifier | CPU (%) | RAM (MB) | Classification time (seconds) | F1-score |
| SMS | CNNc | 176.00% | 264.21 | 3.31 | 0.94 | CNNg | 169.00% | 256.54 | 3.28 | 0.89 | LiDAR | 84.70% | 111.01 | 0.34 | 0.90 | E-mail | CNNc | 353.00% | 2,029.13 | 130.73 | 0.99 | CNNg | 345.80% | 870.11 | 45.35 | 0.98 | LiDAR | 167.50% | 280.37 | 18.44 | 0.93 | 2019 | CNNc | 306.70% | 582.38 | 7.51 | 0.94 | CNNg | 294.10% | 515.59 | 5.94 | 0.90 | LiDAR | 189.60% | 166.84 | 1.71 | 0.94 | 2020 | CNNc | 305.40% | 638.52 | 8.15 | 0.99 | CNNg | 303.40% | 582.70 | 6.99 | 0.97 | LiDAR | 172.80% | 262.40 | 6.51 | 0.94 |
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