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复杂系统与复杂性科学  2017, Vol. 14 Issue (4): 43-50    DOI: 10.13306/j.1672-3813.2017.04.004
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基于网络模体特征攻击的网络抗毁性研究
贾承丰, 韩华, 完颜娟, 吕亚楠
武汉理工大学理学院,武汉 430070
Network Destruction Resistance Based on Network Motif Feature
JIA Chengfeng, HAN Hua, WANYAN Juan, Lü Yanan
Department of Sciences,Wuhan University of Technology,Wuhan 430070,China
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摘要 真实网络如生物神经网络、食物链网络中含有模体结构。但对于这种含有模体特征的网络,并没有一种针对性的攻击策略与之对应,在此基础上提出了模体度代数算法和一种模体攻击失效方式,设计了不同于传统攻击的模体攻击策略。对已检验出的具有明显模体特征的2个仿真网络,5个不同规模的实证网络利用该策略进行模体攻击,并与传统的点攻击方式进行对比研究。仿真结果表明:含有模体特征的网络在模体攻击下的抗毁性明显低于传统的点攻击策略,且在模体特征较明显的网络中模体攻击策略对网络的破坏性更加显著。
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贾承丰
韩华
完颜娟
吕亚楠
关键词 模体攻击策略模体模体度网络抗毁性    
Abstract:Real networks such as biological neural networks, food chain networks contain motif structure.But for this kind of network with the motif characters, there is no corresponded attack strategy. In this paper, we propose a motif degree algebraic algorithm and a motif attack failure mode for this kind of network with the characteristics of the motif structure. We design a model attack strategy which is different from the traditional attack. By using this strategy, two simulation networks and five different size real networks with distinct motif characteristics are simulated and compared with the traditional point attack strategy.The simulation results show that the survivability of the network with the motif feature under the motif attack strategy is obviously lower than traditional point attack strategy.And the motif attacking strategy is more significant to the network with obvious motif characteristics.
Key wordsmotif attack strategy    motif    degree of motif    network survivability
收稿日期: 2017-06-28      出版日期: 2019-01-16
ZTFLH:  N949  
基金资助:国家自然科学基金(71140015,71372135);国家自然科学基金青年科学基金(61303028);中央高校基本科研业务费专项基金(2015zy115)
通讯作者: 韩华(1975),女,博士,教授,主要研究方向为复杂性分析与评价、经济控制与决策。   
作者简介: 贾承丰(1994-),男,硕士研究生,主要研究方向为网络模体。
引用本文:   
贾承丰, 韩华, 完颜娟, 吕亚楠. 基于网络模体特征攻击的网络抗毁性研究[J]. 复杂系统与复杂性科学, 2017, 14(4): 43-50.
JIA Chengfeng, HAN Hua, WANYAN Juan, Lü Yanan. Network Destruction Resistance Based on Network Motif Feature. Complex Systems and Complexity Science, 2017, 14(4): 43-50.
链接本文:  
http://fzkx.qdu.edu.cn/CN/10.13306/j.1672-3813.2017.04.004      或      http://fzkx.qdu.edu.cn/CN/Y2017/V14/I4/43
[1]Barabasi A L, Albert R. Emergence of scaling in random networks[J]. Science, 1999, 286(5439):509.
[2]Crucitti P, Latora V, Marchiori M, et al. Error and attack tolerance of complex networks[J].Nature, 2004, 340(13):388394.
[3]Holme P,Kim B J,Yoon C N,et al. Attack vulnerability of complex networks.[J]. Physical Review E (Statistical, Nonlinear, and Soft Matter Physics),2002,65(5):056109.
[4]Rinaldi S M, Peerenboom J P, Kelly T K. Identifying, understanding, and analyzing critical infrastructure interdependencies[J]. IEEE Control Systems, 2001, 21(6):1125.
[5]黄仁全, 李为民, 董雯,等. 不同攻击策略下作战体系网络抗毁性研究[J]. 复杂系统与复杂性科学, 2012, 09(3):6269.
Huang Renquan, Liweimin, Dong Wen, et al. Research on invulnerability of combat SoS under different attack strategies[J].complex systems and complexity science,2012,09(3):6269.
[6]Milo R,Shen-Orr S,Itzkovitz S, et al. Alon U. Network motifs: simplebuilding blocks of complex networks[J]. Science,2002,298(5594).
[7]Krumov L. Local Structures Determine Performance Within Complex Network[M]. Darmstadt: Suedwestdeutscher Verlag fuerHochschulschriften,2010.
[8]Squartini T, Garlaschelli D. Triadic motifs and dyadic self-organization in the world trade network[M]// Self-Organizing Systems. Springer Berlin Heidelberg, 2012:2435.
[9]韩华, 刘婉璐, 吴翎燕. 基于模体的复杂网络测度量研究[J]. 物理学报, 2013, 62(16):168904168904.
Han Hua, Liu Wanlu, Wu Lingyan. The measurement of complex network base on motif [J].Journal of Physics, 2013, 62(16):168904168904.
[10] Xie W J, Li M X, Jiang Z Q, et al. Triadic motifs in the dependence networks of virtual societies[J]. Scientific Reports, 2014, 4(14):5244.
[11] 吴翎燕, 韩华, 宋宁宁. 基于相关系数和最佳阈值的股票网络模型构建[J]. 复杂系统与复杂性科学, 2013, 10(4):4955.
Wu Lingyan, Han Hua, Song Ningning. The construction of stock network model base on correlation coefficient and optimal threshold[J].complex systems and complexity science, 2013, 10(4):4955.
[12] 张林, 钱冠群, 张莉. 软件系统网络模体及显著性趋势分析[J]. 系统工程理论与实践, 2010, 30(2):361368.
Zhang Lin, Qian Guanqun, Zhangli. Network motif triad significance profile research on software system[J]. Systems Engineeringtheory & Practice, 2010, 30(2):361368.
[13] 贺勤斌, 刘曾荣. 三节点酶网络相互作用的适应性分析[C]// 全国非线性动力学和运动稳定性学术会议. 2011.
He Qinbin, Liuzengrong, Analyse adaptation of interaction threenode enzyme network[C]// The nonlinear dynamics and motion stability of academic conferences. 2011.
[14] Ma W, Trusina A, El-Samad H, et al. Defining network topologies that can achieve biochemical adaptation[J]. Cell, 2009, 138(4):76073.
[15] 蒋长彬. 重庆移动BOSS系统三节点高可用性群集的设计与实现[D]. 重庆大学, 2007.
Jiang Changbin. Design and implementation of a three node high availability cluster for chongqing mobile BOSS system[D]. Chongqing University, 2007.
[16] Ross J. mRNA stability in mammalian cells.[J]. Microbiological Reviews, 1995, 59(3):423.
[17] Han J, Yang J, Yang F. Analysis of failure mode on fouble circuit tangent towers in ice disaster area[J]. Building Structure, 2010.
[18] Wang W X, Chen G. Universal robustness characteristic of weighted networks against cascading failure[J]. Physical Review E Statistical Nonlinear & Soft Matter Physics, 2008, 77(2 Pt 2):026101.
[19] Wernicke S, Rasche F. FANMOD: a tool for fast network motif detection[J]. Bioinformatics, 2006, 22(9):1152.
[20] Erdös P, RényiA. On random graphs I[J]. Publicationes Mathematicae, 1959, 6:290297.
[21] Girvan M, Newman M E J. Community structure in social and biological network. Proc Natl Acad Sci USA.2002: 78217826.
[22] White J G, Southgate E, Thompson J N, et al. "The structure of the nervous system of the nematode C. Elegans", Phil. Trans. R. Soc.London 314, 1340 (1986)
[23] Ebel H, Mielsch L I, Bornholdt S. Scale-free topology of e-mail networks[J]. Phys Rev E Stat Nonlin Soft Matter Phys, 2002, 66(3 Pt 2A):035103.
[24] Bu D, Zhao Y, Cai L, et al. Topological structure analysis of the protein-protein interaction network in budding yeast[J]. Nucleic Acids Research, 2003, 31(9):24432450.
[25] Vladimir B, Andrej M. Pajek data [DB/OL].[20170330] http://vlado.fmf.uni-lj.si/pub/networks/data/,2006.
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