Department of Business Administration, Federal University of Pará, Belém 66075-110, Brazil.
Department of Management Engineering, Universidade Federal de Pernambuco, Recife 50670-901, Brazil.
Sensors (Basel). 2021 Apr 1;21(7):2426. doi: 10.3390/s21072426.
The purpose of this paper is to propose a framework for cybersecurity risk management in telemedicine. The framework, which uses a bow-tie approach for medical image diagnosis sharing, allows the identification, analysis, and assessment of risks, considering the ISO/TS 13131:2014 recommendations. The bow-tie method combines fault tree analysis (FTA) and event tree analysis (ETA). The literature review supported the identification of the main causes and forms of control associated with cybersecurity risks in telemedicine. The main finding of this paper is that it is possible, through a structured model, to manage risks and avoid losses for everyone involved in the process of exchanging medical image information through telemedicine services. Through the framework, those responsible for the telemedicine services can identify potential risks in cybersecurity and act preventively, recognizing the causes even as, in a mitigating way, identifying viable controls and prioritizing investments. Despite the existence of many studies on cybersecurity, the paper provides theoretical contributions to studies on cybersecurity risks and features a new methodological approach, which incorporates both causes and consequences of the incident scenario.
本文旨在为远程医疗中的网络安全风险管理提出一个框架。该框架使用了一种蝴蝶结方法来进行医学图像诊断共享,允许在考虑到 ISO/TS 13131:2014 建议的情况下,对风险进行识别、分析和评估。蝴蝶结方法结合了故障树分析(FTA)和事件树分析(ETA)。文献回顾支持了对远程医疗中与网络安全风险相关的主要原因和控制形式的识别。本文的主要发现是,通过一个结构化的模型,可以对风险进行管理,并避免与通过远程医疗服务交换医学图像信息过程中的所有相关人员的损失。通过该框架,远程医疗服务的负责人可以识别网络安全中的潜在风险,并采取预防措施,即使在以减轻的方式识别可行的控制措施和投资优先级的情况下,也要识别原因。尽管有许多关于网络安全的研究,但本文为网络安全风险的研究提供了理论贡献,并采用了一种新的方法,其中包括事件场景的原因和后果。