A Hybrid Swarm Intelligence Algorithm for Intrusion Detection Using Significant Features

Table 14

Training time of classification algorithms using SFSM and RFSM feature selection methods.

Dataset	SFSM						RFSM
	Naïve Bayes	J4.8	RBF	SVM	ABC	MABC-EPSO	Naïve Bayes	J4.8	RBF	SVM	ABC	MABC-EPSO
DoS + 10% normal	10.20	4.7	3.8	2.86	2.78	2.22	9.95	3.95	3.28	2.59	2.07	1.5
Probe + 10% normal	5.33	3.12	3.05	2.36	2.24	1.87	4.15	3.01	3.19	2.11	1.97	1.69
U2R + 10% normal	4.75	3.81	3.08	2.21	2.16	1.98	4.01	3.46	2.79	1.80	1.78	0.65
R2L + 10% normal	3.98	4.97	3.01	2.46	2.23	2.0	3.12	3.23	2.55	1.42	1.37	1.46