Tabular representation learning for network intrusion detection exhibits strong dataset-model dependency, with supervised methods outperforming unsupervised anomaly detection and limited but possible cross-dataset generalization.
Systematic evaluation of synthetic data augmentation for multi-class netflow traffic
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Evaluating Tabular Representation Learning for Network Intrusion Detection
Tabular representation learning for network intrusion detection exhibits strong dataset-model dependency, with supervised methods outperforming unsupervised anomaly detection and limited but possible cross-dataset generalization.