Targeting attack hypergraph networks

作者全名："Peng, Hao; Qian, Cheng; Zhao, Dandan; Zhong, Ming; Han, Jianmin; Wang, Wei"

作者地址："[Peng, Hao; Qian, Cheng; Zhao, Dandan; Zhong, Ming; Han, Jianmin] Zhejiang Normal Univ, Coll Math & Comp Sci, Jinhua 321004, Zhejiang, Peoples R China; [Wang, Wei] Chongqing Med Univ, Sch Publ Hlth, Chongqing 400016, Peoples R China"

通信作者："Wang, W (通讯作者)，Chongqing Med Univ, Sch Publ Hlth, Chongqing 400016, Peoples R China."

来源：CHAOS

ESI学科分类：PHYSICS

WOS号：WOS:000829482500002

JCR分区：Q1

影响因子：2.9

年份：2022

卷号：32

期号：7

开始页：　

结束页：　

文献类型：Article

关键词：　

摘要："In modern systems, from brain neural networks to social group networks, pairwise interactions are not sufficient to express higher-order relationships. The smallest unit of their internal function is not composed of a single functional node but results from multiple functional nodes acting together. Therefore, researchers adopt the hypergraph to describe complex systems. The targeted attack on random hypergraph networks is still a problem worthy of study. This work puts forward a theoretical framework to analyze the robustness of random hypergraph networks under the background of a targeted attack on nodes with high or low hyperdegrees. We discovered the process of cascading failures and the giant connected cluster (GCC) of the hypergraph network under targeted attack by associating the simple mapping of the factor graph with the hypergraph and using percolation theory and generating function. On random hypergraph networks, we do Monte-Carlo simulations and find that the theoretical findings match the simulation results. Similarly, targeted attacks are more effective than random failures in disintegrating random hypergraph networks. The threshold of the hypergraph network grows as the probability of high hyperdegree nodes being deleted increases, indicating that the network's resilience becomes more fragile. When considering real-world scenarios, our conclusions are validated by real-world hypergraph networks. These findings will help us understand the impact of the hypergraph's underlying structure on network resilience. Published under an exclusive license by AIP Publishing."

基金机构："National Natural Science Foundation of China (NNSFC) [62072412, 61902359, 61702148, 61672468]; Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security [AGK2018001]; Natural Science Foundation of Chongqing [cstc2021jcyj-msxmX0132]"

基金资助正文："ACKNOWLEDGMENTS This work was supported by the National Natural Science Foundation of China (NNSFC) under Grant Nos. 62072412, 61902359, 61702148, and 61672468, in part by the Opening Project of Shanghai Key Laboratory of Integrated Administration Technologies for Information Security (Grant No. AGK2018001), and the Natural Science Foundation of Chongqing (No. cstc2021jcyj-msxmX0132)."