كنفرانس بين المللی مهندسی صنايع و سيستم ها

صفحه اصلی / دوازدهمین كنفرانس بين المللی مهندسی صنايع و سيستم ها

A Dynamic Bayesian Network Framework for Cyber Resilience Assessment in Healthcare IoMT Systems

نویسندگان :

Zohreh Alipour¹ Sayyed Ehsan Monabbati²

1- دانشگاه خاتم 2- دانشگاه الزهرا(س)

کلمات کلیدی :

Dynamic Bayesian network،Internet of medical things،Cyber Resilience،Healthcare Systems،Cyber-attacks،Availability

چکیده :

The rapid expansion of the Internet of Medical Things (IoMT) has led to increased connectivity among medical devices, information systems, and healthcare infrastructures. Assessing cyber resilience has become a fundamental challenge in the management and operation of healthcare infrastructures. This study presents a Dynamic Bayesian Networks (DBN)-based framework for assessing the time-dependent cyber resilience of healthcare systems utilizing the Internet of Medical Things (IoMT). The proposed framework models the causal dependencies among various hospital network assets and captures the temporal propagation of cyberattacks and subsequent recovery process. To represent the stochastic nature of cyber threats, attack occurrence probabilities are modeled using the Weibull distribution, and various scenarios regarding attack severity and recovery capability are examined. Furthermore, system performance is assessed via availability and resilience metrics. To validate the proposed framework, a hospital network comprising IT assets and IoMT equipment was studied. The results demonstrated that increasing the severity of cyberattacks leads to a significant decline in system performance and availability, whereas enhancing recovery capabilities can effectively reduce the time required to return to normal functionality and improve the resilience level. Furthermore, scenario analysis revealed that recovery capabilities become particularly critical under severe cyberattacks. The proposed framework provides a probabilistic and time-dependent approach for analyzing cyber resilience, identifying vulnerabilities, and supporting managerial decision-making to enhance the security and sustainability of IoMT-based healthcare systems.