Table 16 Comparison of the methodology of the proposed model with the deep learning model by Lin et al. [13]
From: A novel time efficient learning-based approach for smart intrusion detection system
| Â | Reference | Proposed |
|---|---|---|
Technique | Deep Learning method using LSTM + AM Reference | Machine learning using hybrid feature selection approach and LightGBM model |
Dataset | CIC-IDS 2018 | CIC-IDS 2018 |
No. of the samples | 2 million random samples | 5.5 million samples |
Skeweness handling | Used SMOTE and under-sampling | Used under-sampling of normal traffic |