论文标题
用于医疗设备的信息安全风险评估的新方法及其评估
A New Methodology for Information Security Risk Assessment for Medical Devices and Its Evaluation
论文作者
论文摘要
随着技术的发展和数字环境的发展，医疗设备正越来越多地与医院网络和互联网联系，从而使它们暴露于新的网络安全威胁。目前，缺乏专门用于医疗设备信息安全风险评估的方法。 在这项研究中，我们介绍了有关医疗设备的信息安全风险评估的威胁识别，基于本体的可能性，严重性分解和风险整合（TLDR）方法。 TLDR方法使用以下步骤：（1）识别医疗设备的潜在脆弱组件，在这种情况下，是四种不同的医学成像设备（MIDS）； （2）确定潜在的攻击，在这种情况下，有23次潜在攻击中MIDS； （3）将发现的攻击映射到已知的攻击本体论中 - 在这种情况下，共同的攻击模式枚举和分类（CAPEC）； （4）在高级医疗保健信息安全专家（ISES）小组的协助下，估计医疗领域中映射的CAPEC的可能性； （5）计算每种攻击的基于CAPEC的可能性估计； （6）将每次攻击分解为多个严重性方面并分配权重； （7）在高级医学专家小组（MES）的协助下，评估每个严重性方面对每种攻击的影响的程度； （8）计算每次攻击的综合严重程度评估；最后，（9）将每种攻击的可能性和严重性整合到其风险中，从而优先考虑。第六到八步的细节超出了当前研究的范围；在当前的研究中，我们用一个步骤代替了他们，其中包括询问MES小组（在这种情况下是放射科医生），以评估每次攻击的总体严重程度，并将其用作其严重性...
As technology advances towards more connected and digital environments, medical devices are becoming increasingly connected to hospital networks and to the Internet, which exposes them, and thus the patients using them, to new cybersecurity threats. Currently, there is a lack of a methodology dedicated to information security risk assessment for medical devices. In this study, we present the Threat identification, ontology-based Likelihood, severity Decomposition, and Risk integration (TLDR) methodology for information security risk assessment for medical devices. The TLDR methodology uses the following steps: (1) identifying the potentially vulnerable components of medical devices, in this case, four different medical imaging devices (MIDs); (2) identifying the potential attacks, in this case, 23 potential attacks on MIDs; (3) mapping the discovered attacks into a known attack ontology - in this case, the Common Attack Pattern Enumeration and Classifications (CAPECs); (4) estimating the likelihood of the mapped CAPECs in the medical domain with the assistance of a panel of senior healthcare Information Security Experts (ISEs); (5) computing the CAPEC-based likelihood estimates of each attack; (6) decomposing each attack into several severity aspects and assigning them weights; (7) assessing the magnitude of the impact of each of the severity aspects for each attack with the assistance of a panel of senior Medical Experts (MEs); (8) computing the composite severity assessments for each attack; and finally, (9) integrating the likelihood and severity of each attack into its risk, and thus prioritizing it. The details of steps six to eight are beyond the scope of the current study; in the current study, we had replaced them by a single step that included asking the panel of MEs [in this case, radiologists], to assess the overall severity for each attack and use it as its severity...
