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International Symposium on Neural Networks

ISNN 2015: Advances in Neural Networks – ISNN 2015 pp 481–488Cite as

A New Virus-Antivirus Spreading Model

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9377))

Abstract

Indeed, countermeasures, as well as computer viruses, could spread in the network. This paper aims to investigate the effect of propagation of countermeasures on viral spread. For the purpose, a new virus-antivirus spreading model is proposed. The global asymptotic stability of the virus-free equilibrium is proved when the threshold is below the unity, and the existence of the viral equilibrium is shown when the threshold exceeds the unity. The influences of different model parameters on the threshold are also analyzed. Numerical simulations imply that the propagation of countermeasures contributes to the suppress of viruses, which is consistent with the fact.

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Author information

Authors and Affiliations

  1. College of Electronic and Information Engineering, Southwest University, 400715, Chongqing, China

    Bei Liu & Chuandong Li

Authors
  1. Bei Liu
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  2. Chuandong Li
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Editor information

Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Xiaolin Hu

  2. Fuzhou University, Fuzhou, China

    Yousheng Xia

  3. School of Information Science and Technology, Sun Yat-sen University, Guangzhou, China

    Yunong Zhang

  4. Chinese Academy of Sciences, Institute of Automation, Beijing, China

    Dongbin Zhao

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© 2015 Springer International Publishing Switzerland

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Liu, B., Li, C. (2015). A New Virus-Antivirus Spreading Model. In: Hu, X., Xia, Y., Zhang, Y., Zhao, D. (eds) Advances in Neural Networks – ISNN 2015. ISNN 2015. Lecture Notes in Computer Science(), vol 9377. Springer, Cham. https://doi.org/10.1007/978-3-319-25393-0_53

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  • DOI: https://doi.org/10.1007/978-3-319-25393-0_53

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-25392-3

  • Online ISBN: 978-3-319-25393-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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