Research Article
ForChaos: Real Time Application DDoS Detection Using Forecasting and Chaos Theory in Smart Home IoT Network
Table 4
Slow-rate attacks results.
| Parameters | Attack Start | DR | TP | FP | FN | Prec. | (sec) | (%) | (%) | (%) | (%) | (%) |
| 20 apps(NoSlow) | 1000 | 100 | 100 | 0 | 0 | 100 |
| 20 apps(NoSlow) | 2000 | 98.6 | 87.5 | 0 | 0 | 100 |
| 20 apps(NoSlow) | 4000 | 100 | 100 | 0 | 0 | 100 |
| 20 apps(Slow) | 1000 | 100 | 100 | 0 | 0 | 100 |
| 20 apps(Slow) | 2000 | 98.6 | 87.5 | 0 | 12.5 | 100 |
| 20 apps(Slow) | 4000 | 98.6 | 100 | 1.53 | 0 | 81.82 |
| 40 apps(NoSlow) | 1000 | 100 | 100 | 0 | 0 | 100 |
| 40 apps(NoSlow) | 2000 | 97.2 | 100 | 3.13 | 0 | 83.33 |
| 40 apps(NoSlow) | 4000 | 94.9 | 100 | 5.34 | 0 | 66.67 |
| 40 apps(Slow) | 1000 | 100 | 100 | 0 | 0 | 100 |
| 40 apps(Slow) | 2000 | 100 | 100 | 0 | 0 | 100 |
| 40 apps(Slow) | 4000 | 100 | 100 | 0 | 0 | 100 |
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