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Impact of Degree Heterogeneity on Attack Vulnerability of Interdependent Networks

机译:程度异质性对相互依赖网络攻击脆弱性的影响

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摘要

The study of interdependent networks has become a new research focus in recent years. We focus on one fundamental property of interdependent networks: vulnerability. Previous studies mainly focused on the impact of topological properties upon interdependent networks under random attacks, the effect of degree heterogeneity on structural vulnerability of interdependent networks under intentional attacks, however, is still unexplored. In order to deeply understand the role of degree distribution and in particular degree heterogeneity, we construct an interdependent system model which consists of two networks whose extent of degree heterogeneity can be controlled simultaneously by a tuning parameter. Meanwhile, a new quantity, which can better measure the performance of interdependent networks after attack, is proposed. Numerical simulation results demonstrate that degree heterogeneity can significantly increase the vulnerability of both single and interdependent networks. Moreover, it is found that interdependent links between two networks make the entire system much more fragile to attacks. Enhancing coupling strength between networks can greatly increase the fragility of both networks against targeted attacks, which is most evident under the case of max-max assortative coupling. Current results can help to deepen the understanding of structural complexity of complex real-world systems.
机译:相互依赖网络的研究已成为近年来的新研究重点。我们专注于相互依赖的网络的一个基本属性:脆弱性。以前的研究主要集中在随机攻击下拓扑特性对相互依赖的网络的影响上,但是度异构性对故意攻击下相互依赖的网络的结构脆弱性的影响尚待探索。为了深入了解度分布尤其是度异质性的作用,我们构建了一个相互依赖的系统模型,该模型由两个网络组成,它们的度异质性程度可以通过调整参数同时控制。同时,提出了一种新的量,可以更好地衡量攻击后相互依赖的网络的性能。数值模拟结果表明,度异质性可以显着增加单个网络和相互依赖网络的脆弱性。而且,发现两个网络之间相互依赖的链接使整个系统更容易受到攻击。增强网络之间的耦合强度可以大大增加两个网络针对目标攻击的脆弱性,这在最大-最大分类耦合的情况下最为明显。当前的结果可以帮助加深对复杂的现实世界系统的结构复杂性的理解。

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