Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System

Table 11

Comparison of ITLBO, ITLBO-JAYA and ITLBO-IPJAYA for the NSL-KDD dataset.

No. of features	Method	MAX. Acc	AVR. Acc	DR	FAR	FNR	F-M	Recall	ER
16	TLBO	0.9639	0.9630	0.9612	0.0449	0.0282	0.9664	0.9717	0.036
	ITLBO	0.9680	0.9678	0.9671	0.0379	0.0268	0.9701	0.9731	0.032
	ITLBO-JAYA	0.9688	0.9685	0.9676	0.0373	0.0258	0.971	0.9741	0.0312
	ITLBO-IPJAYA	0.9708	0.9705	0.9712	0.0331	0.0256	0.9727	0.9742	0.0292
18	TLBO	0.9713	0.971	0.9739	0.0299	0.0275	0.9731	0.9724	0.0286
	ITLBO	0.9718	0.9713	0.9744	0.0292	0.0273	0.9736	0.9726	0.0282
	ITLBO-JAYA	0.9735	0.9733	0.9752	0.0285	0.0247	0.9752	0.9752	0.0265
	ITLBO-IPJAYA	0.9747	0.9746	0.9753	0.0280	0.0221	0.9764	0.9779	0.0252
19	TLBO	0.9738	0.9735	0.9727	0.0313	0.0225	0.9755	0.9774	0.0261
	ITLBO	0.9751	0.9745	0.9737	0.0305	0.0189	0.9769	0.9811	0.0248
	ITLBO-JAYA	0.9759	0.9758	0.9758	0.0278	0.0178	0.9775	0.9791	0.0241
	ITLBO-IPJAYA	0.9772	0.9770	0.9786	0.0245	0.0162	0.9787	0.9787	0.0228
21	TLBO	0.9782	0.9780	0.9742	0.0299	0.0145	0.9797	0.9844	0.0217
	ITLBO	0.9787	0.9784	0.9756	0.0279	0.0144	0.981	0.9846	0.0212
	ITLBO-JAYA	0.9793	0.979	0.9789	0.0273	0.0132	0.9811	0.9867	0.0207
	ITLBO-IPJAYA	0.9802	0.980	0.9792	0.0263	0.0123	0.9812	0.9716	0.0198
22	TLBO	0.9801	0.979	0.9755	0.0284	0.0131	0.9814	0.9868	0.0199
	ITLBO	0.981	0.9805	0.9758	0.0277	0.0117	0.9823	0.989	0.0191
	ITLBO-JAYA	0.9816	0.9814	0.9794	0.0265	0.0114	0.9829	0.989	0.0183
	ITLBO-IPJAYA	0-.9823	0.9821	0.9798	0.0262	0.0102	0.9835	0.9898	0.0177