4.7 Article

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

期刊

CHAOS SOLITONS & FRACTALS
卷 159, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.chaos.2022.112147

关键词

Complex networks; Percolation; Network resilience

资金

  1. National Natural Science Foundation of China [61973143, 71690242, 71974080, 11731014]
  2. Young backbone teachers of Jiangsu Province
  3. Jiangsu Postgraduate Research and Innovation Plan in 2021 [KYCX21_3371]
  4. FACEPE [APQ-0565-1.05/14, APQ-0707-1.05/14]
  5. CAPES
  6. CNPq

向作者/读者索取更多资源

A network of networks is an important class of real coupled networks that portrays the interdependence and coexistence between complex systems. This study investigates the percolation behavior of large-scale network systems, a network of networks with different dependency patterns, under intentional attack with limited information. The results show the effects of coupling strength and the number of known nodes on percolation, critical threshold, and critical coupling strength, as well as a new scaling relationship between 1/p(c) and 1/n for different network configurations.
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 p(c) tends to a steady-state and doesn't change appreciably with n. In particular, we find a new general scaling relationship between 1/p(c) 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.(c) 2022 Published by Elsevier Ltd.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据