Fig 1.
Flow chart of the basic Grasshopper optimisation algorithm.
Fig 2.
Flow chart of the proposed framework.
Table 1.
Average Classification performance using wrapper methods on BoT-IoT and UNSW-NB15.
Table 2.
Evaluation of BoT-IoT and UNSW-NB15 with different scales.
Fig 3.
Comparison of F-measure value for various wrapper techniques on BoT-IoT.
Fig 4.
Comparison of F-measure value for various wrapper techniques on UNSW-NB15.
Fig 5.
Comparison of detection rate for various wrapper techniques on BoT-IoT.
Fig 6.
Comparison of detection rate for various wrapper techniques on UNSW-NB15.
Fig 7.
Comparison of testing execution times for various wrapper techniques on the BoT-IoT.
Fig 8.
Comparison of testing execution times for various wrapper techniques on the UNSW-NB15.
Table 3.
Comparative analysis of the experimental performance, including all attacks of the BoT-IoT and UNSW-NB15 datasets.
Table 4.
Comparative analysis of the proposed in BoT-IoT and UNSW-NB15 datasets.
Fig 9.
ROC curves for wrapper techniques on the BoT-IoT.
Fig 10.
ROC curves for wrapper techniques on the UNSW-NB15.
Table 5.
Description of selected features.
Table 6.
AUROC and AUPR values in BoT-IoT and UNSW-NB15 Datasets.
Table 7.
Summary of statistical results.
Table 8.
Post Hoc Comparison Table for α = 0.05.