Improving the Accuracy of Network Intrusion Detection with Causal Machine Learning

Table 20

Performance of different classifiers in NSL-KDD dataset under different types of cyberattacks.

Algorithm	Detection accuracy under different types of cyberattacks (1, 7)
	1	7
RS-KNN-CFS	0.9886	0.9795
TPE-KNN-CFS	0.9850	0.9778
RS-KNN-IGBS	0.9911	0.9797
TPE-KNN-IGBS	0.9919	0.9812
RS-RF-CFS	0.9877	0.9671
TPE-RF-CFS	0.9837	0.9698
RS-RF-IGBS	0.9939	0.9821
TPE-RF-IGBS	0.9923	0.9810
BRS	0.9959	0.9538
CMLN	0.9983	0.9933