HotSpots: Failure Cascades on Heterogeneous Critical Infrastructure Networks
HotSpots: Failure Cascades on Heterogeneous Critical Infrastructure Networks
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DOI：
10.1145/3132847.3132867
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发表时间：
2017-11
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影响因子：
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通讯作者：
Liangzhe Chen;Xinfeng Xu;S. Lee;Sisi Duan;Alfonso G. Tarditi;S. Chinthavali;B. Prakash
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文献类型：
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作者：
Liangzhe Chen;Xinfeng Xu;S. Lee;Sisi Duan;Alfonso G. Tarditi;S. Chinthavali;B. Prakash
关键基础设施系统，如交通，水和电网系统，对我们的国家安全，经济和公共安全至关重要。最近的事件，如2012年的飓风桑迪，表明不同CI网络之间的相互依赖性如何导致整个系统的灾难性故障。因此，分析这些CI网络，并建立其上的故障级联模型成为一个非常重要的问题。然而，传统模型要么不考虑多个CI或系统的动态，要么对其进行简单建模。在本文中，我们研究这个问题，使用异构网络的观点。我们首先使用国家级数据集构建具有多个组件的异构CI网络。然后，我们研究新的故障最大化问题，这些网络，计算在这样的系统中的关键节点。然后，我们提供热点，这些问题的一个可扩展的和有效的算法，基于仔细的转换。最后，我们进行了广泛的实验，从美国多个州的真实的CIS数据，并表明，我们的方法热点优于非平凡的基线，给出了有意义的结果，我们的方法在提供大规模故障的情况下意识的直接好处。
Critical Infrastructure Systems such as transportation, water and power grid systems are vital to our national security, economy, and public safety. Recent events, like the 2012 hurricane Sandy, show how the interdependencies among different CI networks lead to catastrophic failures among the whole system. Hence, analyzing these CI networks, and modeling failure cascades on them becomes a very important problem. However, traditional models either do not take multiple CIs or the dynamics of the system into account, or model it simplistically. In this paper, we study this problem using a heterogeneous network viewpoint. We first construct heterogeneous CI networks with multiple components using national-level datasets. Then we study novel failure maximization problems on these networks, to compute critical nodes in such systems. We then provide HotSpots, a scalable and effective algorithm for these problems, based on careful transformations. Finally, we conduct extensive experiments on real CIS data from multiple US states, and show that our method HotSpots outperforms non-trivial baselines, gives meaningful results and that our approach gives immediate benefits in providing situational-awareness during large-scale failures.