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Intrusion Detection on UNSW-NB15

98.81Precision

Q-AGNN

Updated 9d ago

Evaluation Results

Method	Links
Q-AGNN 2026.03		98.81	-	-	-	-	-	-	97.87	91.67	94.85	0	16.67	100	-	-
GCN 2026.03		98.81	-	-	-	-	-	-	97.87	91.67	94.85	0	16.67	100	-	-
GAT 2026.03		98.81	-	-	-	-	-	-	97.87	91.67	94.85	0	16.67	100	-	-
GraphSAGE 2026.03		98.81	-	-	-	-	-	-	97.87	91.61	94.85	0	16.67	100	-	-
ClusterGCN 2026.03		98.81	-	-	-	-	-	-	97.87	91.61	94.85	0	16.67	100	-	-
SuperGAT 2026.03		98.81	-	-	-	-	-	-	97.87	91.61	94.85	0	16.67	100	-	-
Ensemble of Deep Learning 2026.03		98.6	-	-	-	-	-	-	99.77	98.6	98.86	-	-	-	-	-
Random Forest 2026.03		98	-	-	-	-	-	-	99.5	97	96	-	-	-	-	-
KAN-LSTM 2026.03		94.5	-	-	-	-	-	-	95.89	93.2	94.01	-	-	-	-	-
TransformerConv 2026.03		90.45	-	-	-	-	-	-	95.74	90.45	90.45	2.44	16.67	97.56	-	-
ODIN 2026.04		85.33	81.72	-	-	-	-	-	-	65.98	73.02	-	-	-	77.48	82.77
EVM 2026.04		84.85	83	-	-	-	-	-	-	51.55	62.59	-	-	-	83.7	83.22
RPM-Net 2026.04		80.22	86.75	-	-	-	-	-	-	80.53	79.5	-	-	-	85.11	85.55
OCN 2026.04		78.26	78.15	-	-	-	-	-	-	77.73	76.05	-	-	-	75.15	78.14
KANs 2026.03		72.42	-	-	-	-	-	-	94.45	72.76	72.56	-	-	-	-	-
ConvKAN 2026.03		70.95	-	-	-	-	-	-	94.31	71.91	70.41	-	-	-	-	-
KANs 2026.03		69.55	-	-	-	-	-	-	93.91	69.58	69.56	-	-	-	-	-
LSTM 2026.03		68.83	-	-	-	-	-	-	93.97	70.28	69.55	-	-	-	-	-
Baseline 2026.04		66.26	78.67	-	-	-	-	-	-	59.12	54.73	-	-	-	79.28	78.67
CNN 2026.03		64.7	-	-	-	-	-	-	93.1	66.1	65.43	-	-	-	-	-
MLP 2026.03		62.67	-	-	-	-	-	-	92.57	62.88	62.82	-	-	-	-	-
GINConv 2026.03		43.62	-	-	-	-	-	-	87.23	50	46.59	0	100	100	-	-
HQC 2025.12		-	-	-	-	0.0566	1.1881	-	-	-	-	-	-	-	-	-