计算机工程

• 安全技术 • 上一篇    下一篇

病毒传播与级联故障相互作用过程的研究

陈利 1,姜东东 2,陆靖桥 3   

  1. (1.上海外国语大学贤达经济人文学院,上海 200083; 2.许继集团有限公司 发电产品研发中心,河南 许昌 461000;3.广东工业大学 计算机学院,广州 510006)
  • 收稿日期:2017-01-03 出版日期:2017-08-15 发布日期:2017-08-15
  • 作者简介:陈利(1980—),男,讲师、硕士,主研方向为网络安全;姜东东,硕士研究生;陆靖桥,硕士。
  • 基金项目:
    广东省科技计划项目(2012B091000173)。

Study on Interaction Process Between Virus Propagation and Cascading Failure

CHEN Li 1,JIANG Dongdong 2,LU Jingqiao 3   

  1. (1.Xianda College of Economics and Humanities Shanghai International Studies University,Shanghai 200083,China;.R&D Center for Power Generation Products,XuJi Group Corporation,Xuchang,Henan 461000,China; 3.School of Computer,Guangdong University of Technology,Guangzhou 510006,China)
  • Received:2017-01-03 Online:2017-08-15 Published:2017-08-15

摘要: 为研究聚类系数对病毒传播与级联故障相互作用的影响,提出一种改进的病毒传播与级联故障相互作用模型。通过改变平均度和三角连接概率调节网络聚类系数,以此观察病毒传播与级联故障相互作用过程。当不考虑三角连接概率时,平均度越小,网络抵制相互作用的能力越强,且区分度越明显,但也会增强级联故障子过程的破坏力。当平均度较小时,三角连接概率越大,网络抵制相互作用的能力越弱。当平均度较大时,不同三角连接概率对应的网络抵制相互作用的效果相似。仿真结果表明,对比单一病毒传播模型,相互作用模型在同一时刻的破坏力更大。

关键词: 聚类系数, 可调聚类系数无标度网络, 病毒传播, 级联故障, 动态相互作用

Abstract: In order to study the influence of clustering coefficient on interaction of virus propagation and cascading failure,an improved interaction model of virus propagation and cascading failure is proposed.Network clustering coefficients are adjusted by changing average degree and probability of triad formation,so as to observe the interaction process of virus propagation and cascading failure.When the probability of triad formation is not considered,the smaller the average degree is,the stronger the ability of the network to resist the interaction is and the more obvious the difference is,but it also enhances the destructive power of the cascading failure sub-procedure.When the average degree is small,the bigger the probability of triad formation is,the weaker the ability of the network to resist interaction is.When the average degree is large,the effects of different probability of triad formation are similar.Simulation results show that compared with the single virus propagation model,the interaction model is more destructive at the same time scale.

Key words: clustering coefficient, scale-free network with adjustable clustering cofficient, virus transmission, cascading failure, dynamic interaction

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