针对核电设施网络攻击的基于风险的绩效方法

Andrew Gisondi, Camille J. Palmer
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引用次数: 0

摘要

本文介绍了一种新方法,该方法提供了一个基于风险知情性能(RIPB)的框架,用于量化与核电设施遭受网络攻击有关的风险。该方法的第一部分包括:1)创建符合 10 CFR 73.54 标准的简化网络基础设施;2)针对网络和网络被动防御的设计基础威胁建模;3)应用模型指标作为贝叶斯分析的输入,以计算电厂控制器被攻击的概率。RAVEN 代码包用于执行随机计算,以量化与利用工厂控制器相关的不确定性,并生成与这些输出相关的基本统计数据,如标准偏差和标准误差。此外,还探索了 ADAPT 等其他工具,这些工具可用于直接对网络拓扑结构进行 DPRA 分析,从而发现新的故障模式或启动事件。RIPB 方法的第二个方面是考虑控制器对物理设备的影响。评估方法是假设可能由被利用的过程控制器的动态特性引起的事故情景,在由 RAVEN 风险分析软件包控制的 RELAP5 模型中启动该事件,并演示可用于量化事故情景后果的算法类型。这项工作中探索的新方法由两部分组成,提供了与网络触发事件相关的不确定性和由该漏洞导致的假定事故的相关后果,以及用于执行分析的示例工具和算法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Risk-Informed Performance-Based methods for cyber-attack on nuclear power facilities
A new approach is described that offers a Risk-Informed Performance-Based (RIPB) framework for quantifying the risk associated with a cyber-attack on a nuclear power-generating facility. The first part of the method involves 1) the creation of a simplified 10 CFR 73.54 compliant cyber infrastructure, 2) modeling of design basis threats against the network and passive defense of the network and 3) applying the model metrics as inputs into a Bayesian analysis to calculate the exploit probability of a plant controller. The RAVEN code package was used to perform a stochastic calculation to quantify the aleatory uncertainty associated with exploiting a plant controller and produce basic statistics associated with those outputs, such as the standard deviation and standard error. Other tools, such as ADAPT, were also explored, which could be leveraged for direct DPRA analysis of network topology, such that new failure modes or initiating events could be discovered. The second aspect of the RIPB method considers the impact of the controller on the physical plant. This evaluation was conducted by postulating an accident scenario possibly caused by the dynamics of an exploited process controller, initiating that event in a RELAP5 model controlled by the RAVEN risk analysis package, and demonstrating the types of algorithms that can be used to quantify the consequences of the accident scenario. The new two-part method explored in this work provides the uncertainty associated with a cyber-initiating event and the associated consequences of a postulated accident resulting from that exploit, as well as example tools and algorithms for performing the analysis.
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