Journal of Cloud Computing

Advances, Systems and Applications

Table 5 Performance comparison of model and baseline

From: MFGAD-INT: in-band network telemetry data-driven anomaly detection using multi-feature fusion graph deep learning

Method	Precision	Recall	F1
RShash	0.7614(0.4444)	0.9999(0.4880)	0.8645(0.4652)
HSTree	0.5475(0.4030)	0.9993(0.4759)	0.7074(0.4367)
ODS	0.8263(0.4967)	0.9999(0.4987)	0.8969(0.4976)
GDN	0.8375(0.5023)	0.9418(0.4965)	0.8866(0.4993)
MFGAD-INT	0.9886(0.5964)	0.9974(0.6274)	0.9942(0.6115)

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