Industrial cyber-physical systems (ICPSs) are widely applied in critical infrastructures such as chemical plants, water distribution networks, and power grids. However, they face various cyberattacks, which may cause physical damage to these industrial facilities. Therefore, ensuring the security of ICPSs is of paramount importance. For this purpose, a new risk assessment method is presented in this paper to quantify the impact of cyberattacks on the physical system of ICPSs. This method helps carry out appropriate attack mitigation measures. The method uses a Bayesian network to model the attack propagation process and infers the probabilities of sensors and actuators to be compromised. These probabilities are fed into a stochastic hybrid system (SHS) model to predict the evolution of the physical process being controlled. Then, the security risk is quantified by evaluating the system availability with the SHS model. The effectiveness of the proposed method is demonstrated with a case study on a hardware-in-the-loop simulation test bed.

中文翻译：

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评估网络攻击对工业网络物理系统的物理影响


工业信息物理系统（ICPS）广泛应用于化工厂、供水网络和电网等关键基础设施。然而，他们面临着各种网络攻击，这可能会对这些工业设施造成物理损害。因此，保障ICPS的安全至关重要。为此，本文提出了一种新的风险评估方法来量化网络攻击对 ICPS 物理系统的影响。此方法有助于执行适当的攻击缓解措施。该方法使用贝叶斯网络对攻击传播过程进行建模，并推断传感器和执行器受到损害的概率。这些概率被输入随机混合系统 (SHS) 模型，以预测受控物理过程的演变。然后，通过SHS模型评估系统可用性来量化安全风险。通过硬件在环仿真测试台的案例研究证明了所提出方法的有效性。