TY - JOUR
T1 - Implementing Anomaly-Based Intrusion Detection for Resource-Constrained Devices in IoMT Networks
AU - Zachos, Georgios
AU - Mantas, Georgios
AU - Porfyrakis, Kyriakos
AU - Rodriguez, Jonathan
PY - 2025/2/17
Y1 - 2025/2/17
N2 - 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.
AB - 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.
KW - anomaly-based intrusion detection
KW - dataset generation
KW - Internet of Medical Things (IoMT)
KW - intrusion detection system (IDS)
KW - machine learning algorithms
KW - novelty detection algorithms
KW - outlier detection algorithms
U2 - 10.3390/s25041216
DO - 10.3390/s25041216
M3 - Article
C2 - 40006445
SN - 1424-8220
VL - 25
JO - Sensors
JF - Sensors
IS - 4
M1 - 1216
ER -