Table 9.

Comparison of models based on respective evaluation metrics for CIC IDS 2018.

Model	Accuracy	Precision	Recall	F1	ROC-AUC Score	Training loss	validation loss	Testing loss
ImmuneNet	99.78	99.77	99.78	99.7	99.786	0.0036	0.0023	0.0025
XGB	99.00	99.03	99.00	99.01	98.98	0.0141	0.0366	0.0389
Random forest	98.81	98.82	98.81	98.81	98.31	0.0989	0.0782	0.0801
Decision trees	98.69	93.41	98.79	96.03	98.731	0.1054	0.1031	0.1053
Logistic regression	87.96	90.8	87.96	88.99	81.537	0.3520	0.2877	0.2798