Research Article
[Retracted] Transfer Learning Auto-Encoder Neural Networks for Anomaly Detection of DDoS Generating IoT Devices
Table 2
Percentage decrease in model accuracy before and after transfer-learning (TL) across device and malware type.
| IoT device | Mirai (% decrease) | Bashlite (% decrease) | Pre-TL | Post-TL | Pre-TL | Post-TL |
| DAD | 18.83 | 0.82 | 40.04 | 1.25 | ECT | 22.15 | 1.37 | 44.65 | 4.24 | P737 | 2.43 | 0.82 | 32.35 | 0.70 | P838 | 2.51 | 0.14 | 32.01 | 1.00 | S1003 | 8.79 | 1.03 | 33.77 | −0.14 | S1002 | 3.97 | 0.37 | 35.22 | 6.08 | PBM | 2.09 | 0.71 | 3.61 | 7.99 | SNH | — | — | 17.02 | −0.12 | END | — | — | 37.07 | 0.01 | Average (%) | 8.68 | 0.75 | 30.64 | 2.33 |
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