Towards robust and efficient intrusion detection in IoMT: a deep learning approach addressing data leakage and enhancing model generalizability

Towards robust and efficient intrusion detection in IoMT: a deep learning approach addressing data leakage and enhancing model generalizability

The Internet of Medical Things (IoMT) brings advanced patient monitoring and predictive analytics to healthcare but also raises cybersecurity and data privacy issues. This paper introduces a deep-learning model for IoMT intrusion detection, utilizing the WUSTL EHMS 2020 dataset, which focuses on cyb...

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Bibliographic Details
Main Authors: Bouke, Mohamed Aly, El Atigh, Hayate, Abdullah, Azizol
Format: Article
Language:en
Published: Springer 2024
Online Access:http://psasir.upm.edu.my/id/eprint/115682/1/115682.pdf
http://psasir.upm.edu.my/id/eprint/115682/
https://link.springer.com/article/10.1007/s11042-024-19916-z?error=cookies_not_supported&code=7d94855e-cdac-492b-b542-f048251f94e3
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http://psasir.upm.edu.my/id/eprint/115682/1/115682.pdf
http://psasir.upm.edu.my/id/eprint/115682/
https://link.springer.com/article/10.1007/s11042-024-19916-z?error=cookies_not_supported&code=7d94855e-cdac-492b-b542-f048251f94e3

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