Table 2.

Comparison results of algorithms in terms of accuracy, Fitness, and the number of selected features.

BLOEO	GOW	HHO	DE	SSA	SCA	Measures	Datasets
0.958	0.943	0.942	0.939	0.922	0.942	Accuracy	NSL-KDD
0.042	0.057	0.058	0.061	0.078	0.058	Fitness
14.3	19.6	16.4	17.2	18.5	14.7	# Features
0.945	0.896	0.889	0.903	0.863	0.891	Accuracy	CICIDS2017
0.055	0.104	0.111	0.097	0.137	0.109	Fitness
18.4	23.5	24.7	27.9	25.5	24.1	# Features
0.976	0.912	0.931	0.880	0.882	0.925	Accuracy	UNSW-NB15
0.024	0.088	0.069	0.120	0.118	0.075	Fitness
10.8	13	11.7	14.6	18.8	12.6	# Features