Chiaradonna Stefano, Jevtić Petar, Lanchier Nicolas
School of Mathematical and Statistical Sciences, Arizona State University, Tempe, Arizona, USA.
Risk Anal. 2023 Dec;43(12):2450-2485. doi: 10.1111/risa.14127. Epub 2023 Apr 10.
Networks like those of healthcare infrastructure have been a primary target of cyberattacks for over a decade. From just a single cyberattack, a healthcare facility would expect to see millions of dollars in losses from legal fines, business interruption, and loss of revenue. As more medical devices become interconnected, more cyber vulnerabilities emerge, resulting in more potential exploitation that may disrupt patient care and give rise to catastrophic financial losses. In this paper, we propose a structural model of an aggregate loss distribution across multiple cyberattacks on a prototypical hospital network. Modeled as a mixed random graph, the hospital network consists of various patient-monitoring devices and medical imaging equipment as random nodes to account for the variable occupancy of patient rooms and availability of imaging equipment that are connected by bidirectional edges to fixed hospital and radiological information systems. Our framework accounts for the documented cyber vulnerabilities of a hospital's trusted internal network of its major medical assets. To our knowledge, there exist no other models of an aggregate loss distribution for cyber risk in this setting. We contextualize the problem in the probabilistic graph-theoretical framework using a percolation model and combinatorial techniques to compute the mean and variance of the loss distribution for a mixed random network with associated random costs that can be useful for healthcare administrators and cybersecurity professionals to improve cybersecurity management strategies. By characterizing this distribution, we allow for the further utility of pricing cyber risk.
十多年来，医疗保健基础设施网络一直是网络攻击的主要目标。仅一次网络攻击，医疗保健机构就可能因法律罚款、业务中断和收入损失而遭受数百万美元的损失。随着越来越多的医疗设备相互连接，出现了更多的网络漏洞，导致更多潜在的被利用情况，这可能会扰乱患者护理并造成灾难性的财务损失。在本文中，我们提出了一个关于典型医院网络遭受多次网络攻击时总损失分布的结构模型。医院网络被建模为一个混合随机图，由各种患者监测设备和医学成像设备作为随机节点组成，以考虑病房的可变占用情况和成像设备的可用性，这些设备通过双向边连接到固定的医院和放射信息系统。我们的框架考虑了医院主要医疗资产可信内部网络中已记录的网络漏洞。据我们所知，在这种情况下，不存在其他关于网络风险总损失分布的模型。我们在概率图论框架中使用渗流模型和组合技术来计算具有相关随机成本的混合随机网络损失分布的均值和方差，这对于医疗保健管理人员和网络安全专业人员改进网络安全管理策略可能是有用的。通过对这种分布进行特征描述，我们为网络风险定价提供了进一步的效用。
