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Structural Vulnerability Analysis in Complex Networks Based on Core Theory

机译:基于核心理论的复杂网络结构脆弱性分析

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Recent studies show that the failures of just a few nodes or edges may disable the operation of the whole network, or even lead to the corruption of the entire system. For a given network and a ratio k, we aim to find out the set with the least number of vulnerable nodes whose removals reduce the connectivity of network structures (suppose to be m) to k*m. We introduce core theory to address this problem. Coritivity is an important measurement to assess the connectivity of network. It is capable of showing not only the difficulty to break down network but also how fragmental the network becomes. We demonstrate that the problem of finding core vertices is an NP-Hard problem. In this case, we propose an approximation algorithm to calculate coritivity of network. The most vulnerable nodes are selected by greedy methods from the set of core nodes found by the previous algorithm. We empirically test our approach on both synthetic and real-world datasets, the results confirm its efficacy compared to random method and three centrality-based algorithms.
机译:最近的研究表明,只有几个节点或边缘的故障可能会禁用整个网络的运行,甚至导致整个系统的损坏。对于给定的网络和比率k,我们的目标是找出脆弱节点数量最少的集合,该脆弱节点的删除将网络结构(假定为m)的连通性降低到k * m。我们介绍了核心理论来解决这个问题。协同性是评估网络连通性的重要指标。它不仅能够显示破坏网络的难度,而且能够显示网络的碎片化程度。我们证明了寻找核心顶点的问题是一个NP-Hard问题。在这种情况下,我们提出一种近似算法来计算网络的共通性。最贪婪的节点是通过贪婪方法从先前算法找到的核心节点集中选择的。我们在合成数据集和真实数据集上都进行了经验测试,结果证实了它与随机方法和三种基于中心度的算法相比的有效性。

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