Hierarchical Flow Model-Based Impact Assessment of Cyberattacks for Critical Infrastructures
Hierarchical Flow Model-Based Impact Assessment of Cyberattacks for Critical Infrastructures
复制标题
基于分层流模型的关键基础设施网络攻击影响评估
DOI：
10.1109/jsyst.2019.2912626
复制
发表时间：
2019-12
影响因子：
4.4
通讯作者：
Fei Li
中科院分区：
文献类型：
--
作者：
Zhu Qianxiang;Qin Yuanqing;Zhou Chunjie;Fei Li
关键基础设施（CI）是国家安全、经济和公共安全的重要组成部分，其防御网络攻击的能力已成为人们关注的焦点。影响评估在这种保护中起着重要作用，它为安全管理人员提供实时情况。CI的评估不仅需要分析网络攻击对任何特定站点的影响，还需要考虑负面影响的传播过程。然而，由于CI及其操作的复杂性，该领域的研究很少同时考虑上述两个方面。针对这一问题，提出了一种基于层次流模型（HFM）的影响评价方法。在这种方法中，提出了一种新的HFM方法，从功能系统的角度来描述一个系统，它结合了流模型和层次知识。利用该方法，建立了一个综合考虑站内信息物理交互、站间相关性和物理网络拓扑结构的CI模型。其次，基于竞争情报模型，提出了一种影响评估方法，以量化竞争情报网络中因影响传播而造成的损失。最后，通过一个燃气供应系统的实例分析，验证了该方法的有效性。
Critical infrastructures (CIs) are essential for the national security, economy, and public safety, whose protection against cyberattacks has become the focus of significant attention. Impact assessment plays an important role in this protection, which provides real-time situations for security managers. The assessment of CIs not only need to analyze the cyberattack's impact on any specific station, but also to consider the spreading process of the negative impact. However, few research in this domain consider the above two aspects simultaneously due to the complexity of CIs and their operation. To tackle this problem, a hierarchical flow model (HFM)-based impact assessment is presented. In this approach, a novel HFM method is proposed to describe a system from a function system perspective, which combines a flow model and hierarchical knowledge. By using this method, a CI model which considers cyber–physical interaction within a station, dependence among stations, and the topological structure of the physical network is established. Next, based on the CI model, an impact assessment is proposed to quantify the loss which is caused by the impact spreading within the CI network. Finally, case studies on a gas supply system are conducted to verify the effectiveness of the proposed approach.
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DOI：
10.1016/0004-3702(94)00043-3
发表时间：
1996
期刊：
Artif. Intell.
影响因子：
--
作者：
J. Larsson
通讯作者：
J. Larsson
DOI：
10.1007/978-3-319-33924-5_5
发表时间：
2017
期刊：
--
影响因子：
--
作者：
B. MacLennan
通讯作者：
B. MacLennan
影响因子：
5.6
作者：
Abdo, H.;Kaouk, M.;Masse, F.
通讯作者：
Masse, F.
影响因子：
8.1
作者：
Ferrario, E.;Pedroni, N.;Zio, E.
通讯作者：
Zio, E.
影响因子：
4.4
作者：
L. Cazorla;Cristina Alcaraz;Javier López
通讯作者：
L. Cazorla;Cristina Alcaraz;Javier López