V1I5P11

Cyber risk Analysis and Assessment of Vulnerabilities in Healthcare: Application of Graph Theory

Samson Adegbenro^1*

Abstract

The increase of digitization of healthcare through electronic health records, telemedicine, and interconnected information systems have improved efficiency in operation as well as exposure cyberattacks. This study adopted the graph theory to model cybersecurity risk across US healthcare provider networks to identify vulnerabilities. Providers were clustered into shared EHR vendors, revealing that large ecosystems such as Epic, Cerner, and eClinicalWorks create a point of failure. Furthermore, central nodes such as Virginia Mason Medical Center and Omni Healthcare emerged as important, while high vulnerable providers like Guidance Center escalates risk due to systemic exposure.  Small nodes particularly providers within eClinicalWorks networks. These findings indicate that cyber risk in a network system is not evenly distributed. The analysis reveals the potential of graph models in exposing spread of risk often overlooked by traditional risk assessments. The study further recommends cybersecurity for central providers including enforcing the accountability of vendors and monitoring bases on network science. This study discusses the role of graph theory in system strength against cyber attacks from ransomware, and other forms of cyber compromise prevalent in the healthcare sector.

Keywords:

graph theory, healthcare provider, risk assessments, cybersecurity