Zachos, Georgios ORCID: https://orcid.org/0000-0001-9130-4605, Mantas, Georgios ORCID: https://orcid.org/0000-0002-8074-0417, Porfyrakis, Kyriakos ORCID: https://orcid.org/0000-0003-1364-0261 and Rodriguez, Jonathan (2025) Implementing anomaly-based intrusion detection for resource-constrained devices in IoMT networks. Sensors, 25 (4):1216. ISSN 1424-8220 (Online) (doi:10.3390/s25041216)

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Abstract

Internet of Medical Things (IoMT) technology has emerged from the introduction of the Internet of Things in the healthcare sector. However, the resource-constrained characteristics and heterogeneity of IoMT networks make these networks susceptible to various types of threats. Thus, it is necessary to develop novel security solutions (e.g., efficient and accurate Anomaly-based Intrusion Detection Systems), considering the inherent limitations of IoMT networks, before these networks reach their full potential in the market. In this paper, we propose an AIDS specifically designed for resource-constrained devices within IoMT networks. The proposed lightweight AIDS leverages novelty detection and outlier detection algorithms instead of conventional classification algorithms to achieve (a) enhanced detection performance against both known and unknown attack patterns and (b) minimal computational costs.

Item Type:	Article
Additional Information:	This article belongs to the Section Sensor Networks.
Uncontrolled Keywords:	anomaly-based intrusion detection, dataset generation, Internet of Medical Things (IoMT), intrusion detection system (IDS), machine learning algorithms, novelty detection algorithms, outlier detection algorithms
Subjects:	Q Science > Q Science (General) Q Science > QA Mathematics > QA75 Electronic computers. Computer science T Technology > T Technology (General)
Faculty / School / Research Centre / Research Group:	Faculty of Engineering & Science > School of Engineering (ENG) Faculty of Engineering & Science
Related URLs:	Publisher
Last Modified:	20 Jun 2025 09:20
URI:	http://gala.gre.ac.uk/id/eprint/50711

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