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.
Intrusion detection and big heterogeneous data: a survey,
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A survey of 28 IoT attacks classified via STRIDE and CVSS, mapped to Process/Code/Communication/Operation/Device vulnerabilities, with mitigations and research gaps.
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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.
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Internet of Things Security: A Survey on Common Attacks
A survey of 28 IoT attacks classified via STRIDE and CVSS, mapped to Process/Code/Communication/Operation/Device vulnerabilities, with mitigations and research gaps.