Recording-Aware Evaluation of Multimodal OT Intrusion Detection

Reported by arXiv cs.CR (Mustafa Umut Ozbek, Khalil El-Khatib, Li Yang)

Summary by Cyber Security News20 Oct 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.24128

arXiv:2610.24128v1 Announce Type: new Abstract: Machine-learning-based intrusion detection systems (IDSs) for operational technology (OT) are commonly evaluated on benchmark datasets in which normal and attack data are collected in separate recordings. In such settings, high performance may reflect recording-associated differences as well as attack behavior.

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