Table 3.

Comparison results of algorithms in terms of precision, sensitivity, specificity, and F-score.

BLOEO	GOW	HHO	DE	SSA	SCA	Measures	Datasets
0.982	0.959	0.962	0.955	0.951	0.964	Precision	NSL-KDD
0.957	0.936	0.922	0.901	0.914	0.931	Sensitivity
0.977	0.950	0.953	0.938	0.947	0.957	Specificity
0.969	0.947	0.941	0.927	0.932	0.947	F-score
0.971	0.933	0.912	0.932	0.892	0.922	Precision	CICIDS2017
0.954	0.900	0.890	0.911	0.869	0.901	Sensitivity
0.966	0.924	0.898	0.925	0.887	0.920	Specificity
0.962	0.916	0.900	0.921	0.880	0.911	F-score
1.000	0.939	0.958	0.916	0.920	0.949	Precision	UNSW-NB15
0.973	0.918	0.936	0.934	0.911	0.956	Sensitivity
0.983	0.928	0.944	0.908	0.918	0.931	Specificity
0.986	0.928	0.946	0.924	0.915	0.952	F-score