辐射瘤学 勒索软件攻击响应 风险分析 使用故障模式和效果分析 分析
Yevgeniy Vinogradskiy1, Leah Schubert2, Amy Taylor1
1Department of Radiation Oncology, Thomas Jefferson University, Philadelphia Pennsylvania.
Practical radiation oncology
|March 20, 2024
概括
勒索软件攻击通过禁用关键的记录和验证 (R&V) 系统,显著增加了放射瘤学中的患者安全风险. 这项研究量化了事故风险的71%上升,突出了提高准备能力的关键故障模式.
科学领域:
- 医学物理 医学物理
- 辐射瘤学 辐射瘤学
- 医疗信息学 医疗信息学
背景情况:
- 勒索软件攻击对医疗保健构成越来越大的威胁,特别是辐射瘤学.
- 以前的研究主要由病例报告组成,缺乏定量风险评估.
- 网络攻击期间的患者安全仍然是一个关键问题.
研究的目的:
- 在辐射瘤学中模拟勒索软件攻击期间量化患者安全风险.
- 识别与记录和验证 (R&V) 系统损失相关的关键故障模式.
- 为提高勒索软件在放射治疗中的弹性提供信息的策略.
主要方法:
- 使用了多学科团队的故障模式和影响分析 (FMEA).
- 开发了流程地图来模拟勒索软件场景,重点关注R&V系统不可用.
- 使用风险优先数 (RPN) 评分量化风险,比较带有和没有R&V功能的场景.
主要成果:
- 当R&V功能被禁用时,风险优先次数 (RPN) 得分增加了71% (38%-96%).
- 发现的关键失效模式包括错误的患者识别和错误的治疗跟踪.
- 模拟结果显示,在计划修改和初始治疗过程中存在重大安全漏洞.
结论:
- 勒索软件攻击大大提高了辐射瘤学事件的风险.
- 确定故障模式的优先考虑对于有效的勒索软件准备工作至关重要.
- 这些定量数据支持未来的勒索软件弹性研究和协议的开发.
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