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

Table 14

Comparison with the existing work for the NSL-KDD dataset.

Ref.	Method	Dataset	Acc.	DR	FAR
[35]	Two-stage classifier	NSL-KDD	96.38	N.G	N.G
[36]	Hypergraph-based genetic algorithm and SVM	NSL-KDD	0.975	0.9714	0.83
[8]	PSO and SVM	NSL-KDD	0.9784	0.9723	0.87
[37]	Chi-square and SVM	NSL-KDD	0.98	N.G	0.13
[38]	SVM and hybrid PSO	NSL-KDD	0.7341	0.6628	2.81
[39]	SVM and feature selection	NSL-KDD	0.90	N.G	N.G
[40]	SVM and GA	NSL-KDD	0.975	N.G	N.G
TLBO-SVM	TLBO and SVM	NSL-KDD	0.9801	0.9755	0.0284
ITLBO-SVM	Improved TLBO and SVM	NSL-KDD	0.981	0.9758	0.0277
ITLBO-JAYA-SVM	Improved TLBO, improved JAYA and SVM	NSL-KDD	0.9816	0.9794	0.0265
ITLBO-IPJAYA-SVM	Improved TLBO, improved JAYA and SVM	NSL-KDD	0.9823	0.9798	0.0262