Percolation behaviors of a network of networks under intentional attack with limited information

相互依存的网络 缩放比例 复杂网络 计算机科学 耦合强度 渗透(认知心理学) 弹性(材料科学) 渗流阈值 相互依存 理论计算机科学 统计物理学 数学 物理 心理学 几何学 量子力学 神经科学 万维网 政治学 法学 电阻率和电导率 凝聚态物理 热力学
作者
Gaogao Dong,Yun Luo,Yangyang Liu,Fan Wang,Huanmei Qin,André L. M. Vilela
出处
期刊:Chaos Solitons & Fractals [Elsevier BV]
卷期号:159: 112147-112147 被引量:10
标识
DOI:10.1016/j.chaos.2022.112147
摘要

As an important class of real coupled networks, a network of networks portrays the interdependence and coexistence between complex systems. Especially for large networks, one may not know the information of all nodes in the network, only limited information can be known. Motivated by this, we here propose a new attack strategy, the intentional attack with limited information, where the limited information represents that the information of only n nodes is known. Further, we investigate the percolation behavior of large-scale network systems, a network of networks with different dependency patterns, under intentional attack with limited information. We show analytically and numerically how the coupling strength q and n affect the percolation, critical threshold, and the critical coupling strength. Furthermore, as n increases, the results suggest that the system becomes more vulnerable and different to protect. But when n reaches a critical value, the critical threshold pc tends to a steady-state and doesn't change appreciably with n. In particular, we find a new general scaling relationship between 1/pc and 1/n for different network configuration. Our model sheds light on the resilience of large-scale interdependent networks under limited information attacks, and provides helpful insights into designing robust real-world systems.

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