SECURE NETWORK SEGMENTATION OF MEDICAL IOT AND LEGACY BIOMEDICAL DEVICES IN HOSPITAL ENVIRONMENT
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2026
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| author | Nuha Lutfi, Sarun Puthanpurayil Kaliyarmban, Kashif Aziz, Abdul Aziz Abdul Qader, Mohammed Abdul Haq Mujahed, Mohamed Izeldin Siddig Malik, Shigul Thundiyil, Syed Muhammad Ali Haider, Aya Ahmad Khaleel Abuhmaid |
| author_facet | Nuha Lutfi, Sarun Puthanpurayil Kaliyarmban, Kashif Aziz, Abdul Aziz Abdul Qader, Mohammed Abdul Haq Mujahed, Mohamed Izeldin Siddig Malik, Shigul Thundiyil, Syed Muhammad Ali Haider, Aya Ahmad Khaleel Abuhmaid |
| contents | <p><strong><em><span>The rapid adoption of Medical Internet of Things (MIoT) devices in hospital settings has resulted in better clinical efficiency, patient monitoring, and data-driven decision-making. Nevertheless, this integration has also increased the risk of cyberattacks on healthcare networks, especially because modern MIoT devices are used together with old biomedical equipment that often does not have any security features. Most legacy systems were not designed for interconnected environments, thus making them very open to malware infection, ransomware attacks, and unauthorized access. Hence, secure network segmentation has been considered a vital approach to reducing these risks while maintaining the clinical aspect and regulatory compliance. This study discusses secure network segmentation techniques for separating MIoT and legacy biomedical devices in hospital infrastructure. This article is based on existing research in healthcare cybersecurity, zero-trust networking, and medical device risk management, and evaluates the application of architectural models, segmentation techniques, and policy-based controls in heterogeneous clinical environments. The authors show how logical segmentation, access control enforcement, and monitoring can address lateral movement threats without stopping medical workflows. By merging insights from previous studies, this study adds to the ongoing dialogue on healthcare cybersecurity by closing the security gap between the latest MIoT deployments and outdated medical systems, thus laying a path for resilient and scalable hospital network designs.</span></em></strong></p> |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_19113684 |
| institution | Zenodo |
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| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | SECURE NETWORK SEGMENTATION OF MEDICAL IOT AND LEGACY BIOMEDICAL DEVICES IN HOSPITAL ENVIRONMENT Nuha Lutfi, Sarun Puthanpurayil Kaliyarmban, Kashif Aziz, Abdul Aziz Abdul Qader, Mohammed Abdul Haq Mujahed, Mohamed Izeldin Siddig Malik, Shigul Thundiyil, Syed Muhammad Ali Haider, Aya Ahmad Khaleel Abuhmaid Medical Internet of Things (Miot), Network Segmentation, Healthcare Cybersecurity, Legacy Biomedical Devices, Hospital Network Security, Zero-Trust Architecture. <p><strong><em><span>The rapid adoption of Medical Internet of Things (MIoT) devices in hospital settings has resulted in better clinical efficiency, patient monitoring, and data-driven decision-making. Nevertheless, this integration has also increased the risk of cyberattacks on healthcare networks, especially because modern MIoT devices are used together with old biomedical equipment that often does not have any security features. Most legacy systems were not designed for interconnected environments, thus making them very open to malware infection, ransomware attacks, and unauthorized access. Hence, secure network segmentation has been considered a vital approach to reducing these risks while maintaining the clinical aspect and regulatory compliance. This study discusses secure network segmentation techniques for separating MIoT and legacy biomedical devices in hospital infrastructure. This article is based on existing research in healthcare cybersecurity, zero-trust networking, and medical device risk management, and evaluates the application of architectural models, segmentation techniques, and policy-based controls in heterogeneous clinical environments. The authors show how logical segmentation, access control enforcement, and monitoring can address lateral movement threats without stopping medical workflows. By merging insights from previous studies, this study adds to the ongoing dialogue on healthcare cybersecurity by closing the security gap between the latest MIoT deployments and outdated medical systems, thus laying a path for resilient and scalable hospital network designs.</span></em></strong></p> |
| title | SECURE NETWORK SEGMENTATION OF MEDICAL IOT AND LEGACY BIOMEDICAL DEVICES IN HOSPITAL ENVIRONMENT |
| topic | Medical Internet of Things (Miot), Network Segmentation, Healthcare Cybersecurity, Legacy Biomedical Devices, Hospital Network Security, Zero-Trust Architecture. |
| url | https://doi.org/10.5281/zenodo.19113684 |