Research Article
[Retracted] Research on Boruta-ET-Based Anomalous Traffic Detection Model
Table 7
Comparison of the accuracy of the model proposed in this study with other algorithms.
| Author | Method | Acc (%) |
| Ahmim et al. [15] | Rep + RF | 96.67 | Wang [16] | PCA + SVM | 92.91 | Ustebay et al. [17] | AutoEncoder + DNN | 96.71 | Di and Li [18] | SVM + DBN | 92.56 | Zhang et al. [19] | Confidence + DNN | 93.80 |
| Other comparison algorithms in this article | NB | 86.24 | LGBM | 82.09 | DT | 98.87 | Xgboost | 95.58 | RF | 96.44 | DNN | 92.02 |
| The method proposed in this article | Boruta-ET | 99.80 |
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