A semi-supervised temporal framework for cloud network intrusion detection that combines supervised learning with consistency regularization and selective pseudo-labeling to improve robustness against adversarial contamination and temporal drift.
Outside the Closed World: On Using Machine Learning for Network Intrusion Detection,
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Robust Semi-Supervised Temporal Intrusion Detection for Adversarial Cloud Networks
A semi-supervised temporal framework for cloud network intrusion detection that combines supervised learning with consistency regularization and selective pseudo-labeling to improve robustness against adversarial contamination and temporal drift.