ATTACK VULNERABILITY OF FRACTAL SCALE-FREE NETWORK

Fractals Pub Date : 2024-04-13 DOI:10.1142/s0218348x24500695
FEIYAN GUO, LIN QI, YING FAN
{"title":"ATTACK VULNERABILITY OF FRACTAL SCALE-FREE NETWORK","authors":"FEIYAN GUO, LIN QI, YING FAN","doi":"10.1142/s0218348x24500695","DOIUrl":null,"url":null,"abstract":"<p>An in-depth analysis of the attack vulnerability of fractal scale-free networks is of great significance for designing robust networks. Previous studies have mainly focused on the impact of fractal property on attack vulnerability of scale-free networks under static node attacks, while we extend the study to the cases of various types of targeted attacks, and explore the relationship between the attack vulnerability of fractal scale-free networks and the fractal dimension. A hierarchical multiplicative growth model is first proposed to generate scale-free networks with the same structural properties except for the fractal dimension. Furthermore, the fractal dimension of the network is calculated using two methods, namely, the box-covering method and the cluster-growing method, to exclude the possibility of differences in conclusions caused by the methods of calculating the fractal dimension for the subsequent relationship analysis. Finally, four attack strategies are used to attack the network, and the network performance is quantitatively measured by three structural indicators. Results on model networks show that compared to non-fractal modular networks, fractal scale-free networks are more robust to both static and dynamic targeted attacks on nodes and links, and the robustness of the network increases as the fractal dimension decreases. However, there is a cost in that as the fractal dimension decreases, the network becomes less efficient and more vulnerable to random failures on links. These findings contribute to a deeper understanding of the impact of fractal property on scale-free network performance and may be useful for designing resilient infrastructures.</p>","PeriodicalId":501262,"journal":{"name":"Fractals","volume":"91 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fractals","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/s0218348x24500695","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

An in-depth analysis of the attack vulnerability of fractal scale-free networks is of great significance for designing robust networks. Previous studies have mainly focused on the impact of fractal property on attack vulnerability of scale-free networks under static node attacks, while we extend the study to the cases of various types of targeted attacks, and explore the relationship between the attack vulnerability of fractal scale-free networks and the fractal dimension. A hierarchical multiplicative growth model is first proposed to generate scale-free networks with the same structural properties except for the fractal dimension. Furthermore, the fractal dimension of the network is calculated using two methods, namely, the box-covering method and the cluster-growing method, to exclude the possibility of differences in conclusions caused by the methods of calculating the fractal dimension for the subsequent relationship analysis. Finally, four attack strategies are used to attack the network, and the network performance is quantitatively measured by three structural indicators. Results on model networks show that compared to non-fractal modular networks, fractal scale-free networks are more robust to both static and dynamic targeted attacks on nodes and links, and the robustness of the network increases as the fractal dimension decreases. However, there is a cost in that as the fractal dimension decreases, the network becomes less efficient and more vulnerable to random failures on links. These findings contribute to a deeper understanding of the impact of fractal property on scale-free network performance and may be useful for designing resilient infrastructures.

分形无标度网络的攻击漏洞
深入分析分形无标度网络的攻击脆弱性对设计鲁棒性网络具有重要意义。以往的研究主要集中在分形特性对静态节点攻击下无标度网络攻击脆弱性的影响,而我们将研究扩展到了各种类型的定向攻击情况,并探讨了分形无标度网络攻击脆弱性与分形维度之间的关系。我们首先提出了一种分层乘法增长模型,以生成除分形维度外具有相同结构特性的无标度网络。此外,还采用两种方法计算网络的分形维度,即盒盖法和聚类增长法,以排除因计算分形维度的方法不同而导致结论差异的可能性,为后续的关系分析提供依据。最后,采用四种攻击策略对网络进行攻击,并通过三个结构指标对网络性能进行定量测量。对模型网络的研究结果表明,与非分形模块网络相比,分形无标度网络对节点和链路的静态和动态定向攻击都具有更强的鲁棒性,而且网络的鲁棒性随着分形维度的减小而增强。然而,随着分形维度的降低,网络的效率也会降低,更容易受到链路随机故障的影响。这些发现有助于加深理解分形特性对无标度网络性能的影响,并可能有助于设计弹性基础设施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信