Optimizing Intrusion Detection in IoMT Networks Through Interpretable and Cost-Aware Machine Learning

Optimizing Intrusion Detection in IoMT Networks Through Interpretable and Cost-Aware Machine Learning

The rise of the Internet of Medical Things (IoMT) has enhanced healthcare delivery but also exposed critical cybersecurity vulnerabilities. Detecting attacks in such environments demands accurate, interpretable, and cost-efficient models. This paper addresses the critical challenges in network secur...

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Bibliographic Details
Main Authors: Abdelatif Hafid, Mohamed Rahouti, Mohammed Aledhari
Format: Article
Language:English
Published: MDPI AG 2025-05-01
Series:Mathematics
Subjects:
machine learning
IoMT
network security
XGBoost
late fusion
SHAP
Online Access:https://www.mdpi.com/2227-7390/13/10/1574
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