Dart Martin, Ahmed Mohiuddin
School of Science, Edith Cowan University, Joondalup, WA, Australia.
Digit Health. 2023 Jul 30;9:20552076231191095. doi: 10.1177/20552076231191095. eCollection 2023 Jan-Dec.
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.
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.
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.
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.
本文利用统一建模语言(UML)的结构和简洁性,为澳大利亚大型医疗服务提供商提出了一种新颖的网络安全风险治理框架和本体论。该框架旨在减轻以下风险领域的影响:(1)网络攻击,(2)事件,(3)数据泄露,以及(4)数据披露。
采用由实证证据发现和现象学审查组成的混合方法,获取现有文献以确认基线本体论定义。这些定义辅以澳大利亚政府报告、专业标准出版物以及涵盖网络安全、数据泄露报告和医疗治理的立法。对医疗网络安全事件的历史案例进行了审查,并提出了一个网络风险治理UML,通过一个单一的、简化的本体图来管理已定义的问题领域。
生成了“网络安全”的明确定义以及“CYBER - AIDD”风险模型。经确认,在5年期间影响澳大利亚医疗行业的网络安全事件具体案例为N = 929起,其中人为因素是最大的促成因素。CYBER - AIDD UML模型展示了一个跨四个已定义类别的工作流程,为实施减轻针对已证实威胁的风险所需的控制措施提供了清晰的方法。
医疗行业的网络安全治理很复杂,部分原因是关键术语和风险缺乏明确性,这导致运营结果一直不佳。使用简单的UML模型专注于最关键的风险途径,有助于描述这些风险并围绕它们设计治理控制措施。