Assessing the Physical Impact of Cyberattacks on Industrial Cyber-Physical Systems
Assessing the Physical Impact of Cyberattacks on Industrial Cyber-Physical Systems
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DOI：
10.1109/tie.2018.2798605
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发表时间：
2018-01
影响因子：
7.7
通讯作者：
Kaixing Huang;Chunjie Zhou;Yu-Chu Tian;Shuanghua Yang;Yuanqing Qin
中科院分区：
文献类型：
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作者：
Kaixing Huang;Chunjie Zhou;Yu-Chu Tian;Shuanghua Yang;Yuanqing Qin
工业网络物理系统(ICPS)广泛应用于化工厂、给水管网、电网等关键基础设施中。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，确保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。该方法有助于实施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，并推断出传感器和执行器受到攻击的概率。这些概率被输入到随机混合系统(SHS)模型中，以预测被控物理过程的演化。然后，利用SHS模型对系统可用性进行评估，量化安全风险。以半实物仿真试验台为例，验证了该方法的有效性。
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.