Enhancing Security of IoT Enabled Smart Healthcare Clinics Using MUD
Vaishali Soni, Deepika Kukreja, Amarjit Malhotra · Journal of Mobile Multimedia · 2025
The rapid adoption of the Internet of Things (IoT) is changing almost all aspects of life and the use of these technologies is increasing in different sectors such as education, healthcare and manufacturing. Within the healthcare sector, smart clinics are coming up as new generation of healthcare facilities connected with IoT-enabled medical devices like cameras, diagnostic devices and sensors to aid in patient care. However, this paper has established that security is a major concern in the use of IoT devices due to the fact that most of them are unprotected and therefore prone to attacks. In response to this problem, the Internet Engineering Task Force (IETF) suggested the Manufacturer Usage Description (MUD) framework to specify safe communication behaviors for IoT devices. This paper proposes the adoption of MUD profiling to improve the security position of IoT powered smart clinics. When MUD profiles were applied to devices in the ECU-IoHT dataset, we were able to get a better anomaly detection using Machine Learning (ML) models. Random Forest and XGBoost classifiers had a gain in accuracy of 1.43% and 1.74% respectively, MLP increased by 2.80% and CatBoost increased by 0.51%. These results show that MUD based security mechanisms can be useful in protecting IoT based healthcare environments.