A Quantitative Risk Assessment Framework for the Cybersecurity of Networked Medical Devices


  • Maureen Van Devender University of South Alabama
  • Jeffrey Todd McDonald




Medical devices are increasingly the source of cybersecurity exposure in healthcare organizations. Research and media reports demonstrate that the exploitation of cybersecurity vulnerabilities can have significant adverse impacts ranging from the exposure of sensitive and personally identifiable patient information to compromising the integrity and availability of clinical care. The results can include identity theft and negative health consequences, including loss of life. Assessing the risk posed by medical devices can provide healthcare organizations with information to prioritize mitigation efforts. However, producing accurate risk assessments in environments with both sparse historical data and a lack of validation regarding the accuracy of forecasts is particularly challenging.

We present a risk assessment framework for quantifying the risk posed by connected medical devices in trusted healthcare networks. Our framework is built upon prominent existing frameworks and guidance for general risk assessment and cybersecurity risk assessment. We add a method for quantifying risk, which to our knowledge is novel in the context of medical devices on trusted networks. The framework provides a structure for combining publicly available information along with expert elicitation about threats, vulnerabilities, and consequences. The goal is to provide healthcare organizations with actionable information for prioritizing and mitigating risks in medical devices.