Document Type
Journal Article
Publication Title
Digital Health
Publisher
SAGE
School
School of Science
RAS ID
60294
Abstract
Purpose: This paper proposes a novel cyber security risk governance framework and ontology for large Australian healthcare providers, using the structure and simplicity of the Unified Modelling Language (UML). This framework is intended to mitigate impacts from the risk areas of: (1) cyber-attacks, (2) incidents, (3) data breaches, and (4) data disclosures. Methods Using a mixed-methods approach comprised of empirical evidence discovery and phenomenological review, existing literature is sourced to confirm baseline ontological definitions. These are supplemented with Australian government reports, professional standards publications and legislation covering cyber security, data breach reporting and healthcare governance. Historical examples of healthcare cyber security incidents are reviewed, and a cyber risk governance UML presented to manage the defined problem areas via a single, simplified ontological diagram. Results A clear definition of ‘cyber security’ is generated, along with the ‘CYBER-AIDD’ risk model. Specific examples of cyber security incidents impacting Australian healthcare are confirmed as N = 929 over 5 years, with human factors the largest contributor. The CYBER-AIDD UML model presents a workflow across four defined classes, providing a clear approach to implementing the controls required to mitigate risks against verified threats. Conclusions The governance of cyber security in healthcare is complex, in part due to a lack of clarity around key terms and risks, and this is contributing to consistently poor operational outcomes. A focus on the most essential avenues of risk, using a simple UML model, is beneficial in describing these risks and designing governance controls around them.
DOI
10.1177/20552076231191095
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Comments
Dart, M., & Ahmed, M. (2023). CYBER-AIDD: A novel approach to implementing improved cyber security resilience for large Australian healthcare providers using a unified modelling language ontology. Digital Health, 9, 1-15. https://doi.org/10.1177/20552076231191095