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papersTODAY 04:00 UTC

Explainable Hybrid Feature Selection Proposed for Intrusion Detection in IoMT

A new arXiv paper describes an intrusion detection system designed for Internet of Medical Things networks, where devices are diverse and computing power is limited. The approach combines hybrid feature selection with explainability so that real-time traffic can be screened while keeping the model's decisions interpretable. The authors frame resource constraints and the need for timely analysis as the main obstacles the method targets.

arXiv explainable-ai feature selection internet-of-medical-things intrusion-detection resource-constrained-computing

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arXiv cs.LGExplainable Hybrid Feature Selection for Intrusion Detection in Internet of Medical Things Environments ↗TODAY 04:00 UTC