用平均网络流度量网络鲁棒性
Measuring Network Robustness by Average Network Flow
摘要：
互联网骨干网和电网等基础设施网络对我们的日常生活至关重要。随着网络攻击的普遍存在，衡量其健壮性已成为一个重要问题。迄今为止，已经提出了许多鲁棒性度量。鲁棒性度量需要具有以下三个性质：考虑全局网络拓扑，在添加链路时严格增加，以及在稀疏网络上的节点数量方面具有二次复杂性。本文提出用平均网络流（ANF）作为鲁棒性度量，证明了它是严格递增的，并利用Gomory-Hu树给出了一个计算ANF的二次复杂度算法。因此，ANF本质上考虑到全球网络拓扑结构，ANF是一个新的鲁棒性度量满足这三个属性。此外，本文还将ANF与现有的7个代表性指标进行了比较，表明每个指标都有自己的特点，因此在衡量网络鲁棒性方面没有灵丹妙药，建议将几个指标一起应用以获得全面的看法。最后，通过实验的情况下，网络拓扑保持相同数量的节点和链接，一些有趣的行为的鲁棒性度量报告。
英文摘要：
Infrastructure networks such as the Internet backbone and power grids are essential for our everyday lives. With the prevalence of cyber-attacks on them, measuring their robustness has become an important issue. To date, many robustness metrics have been proposed. It is desirable for a robustness metric to possess the following three properties: considering global network topologies, strictly increasing upon link additions, and having a quadratic complexity in terms of the number of nodes on sparse networks. This paper proposes to use Average Network Flow (ANF) as a robustness metric, and proves that it increases strictly, and gives an algorithm to compute ANF with a quadratic complexity by leveraging Gomory-Hu trees. Thus, with ANF intrinsically considering global network topologies, ANF is unveiled to be a new robustness metric satisfying those three properties. Moreover, this paper compares ANF with seven existing representative metrics, showing that each metric has its own characteristics, so there is no silver bullet in measuring network robustness and it is recommended to apply several metrics together to gain a comprehensive view. Finally, by experimenting on the scenarios in which network topologies preserve the same numbers of nodes and links, some interesting behaviors of robustness metrics are reported.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
