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Evaluation the Robustness of Iot Intrusion Detection Models in Adversarial Attack Environments
32/32 checkable references clean · checked 2026-08-27
Every reference with a DOI in the deposited reference list resolved to a known work in Crossref or DataCite at the dated check, and none carried a retraction, withdrawal, or removal notice.
36 without a DOI — not checked. A reference deposited without a DOI is never matched by title or guessed at; it stays outside the checked set, and this line discloses that.
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The 36 references without a DOI — listed, not checked
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no DOI — not checkedIDSGAN: Generative Adversarial Networks for Attack Generation Against Intrusion Detection
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no DOI — not checkedEvading Botnet Detectors Based on Flows and Random Forest with Adversarial Samples
no DOI — not checkedAnalyzing Adversarial Attacks against Deep Learning for Intrusion Detection in IoT Networks
no DOI — not checkedThe robust deep learning-based schemes for intrusion detection in Internet of Things environments
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no DOI — not checkedA Network Function Virtualization System for Detecting Malware in Large IoT Based Networks
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