Table 2 Bot-IoT dataset results.
From: A lightweight framework to secure IoT devices with limited resources in cloud environments
Model | Accuracy (%) | F1-Score | FPR (%) | Memory (MB) | Energy (W) | Inference (ms) |
|---|---|---|---|---|---|---|
Proposed framework | 97.9 | 0.96 | 0.9 | 13.1 | 0.48 | 0.9 |
Random forest | 95.8 | 0.93 | 1.5 | 88.6 | 1.85 | 2.7 |
SVM (RBF kernel) | 93.5 | 0.90 | 2.8 | 40.2 | 1.25 | 5.5 |
k-NN (k=5) | 91.2 | 0.87 | 3.6 | 47.8 | 1.55 | 4.0 |
Logistic regression | 89.7 | 0.84 | 5.2 | 23.5 | 0.95 | 1.3 |
Gradient boosting | 96.3 | 0.94 | 1.3 | 65.7 | 1.45 | 2.3 |
Neural network | 96.0 | 0.93 | 1.8 | 150.1 | 2.20 | 9.0 |
