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Optimal Antivirus Protection Strategy in Computer Networks

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Book cover Analytical and Computational Methods in Probability Theory (ACMPT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10684))

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Abstract

We construct a mathematical model of anti-virus protection of local area networks. The model belongs to the class of regenerative processes. To protect the network from the external attacks of viruses and the spread of viruses within the network we apply two methods: updating antivirus signatures and reinstallings of operating systems (OS). Operating systems are reinstalled in the case of failure of any of the computers (non-scheduled emergent reinstalling) or at scheduled time moments. We consider a maximization problem of an average unit income. The cumulative distribution function (CDF) of the scheduled intervals between complete OS reinstallings is considered as a control. We prove that the optimal CDF has to be degenerate, i.e., it is localized at a point \(\tau \).

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Authors and Affiliations

  1. National Research University Higher School of Economics, Moscow Institute of Electronics and Mathematics, Moscow, Russia

    Yulia Grishunina & Larisa Manita

Authors
  1. Yulia Grishunina
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  2. Larisa Manita
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Corresponding author

Correspondence to Larisa Manita .

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Editors and Affiliations

  1. Department of Applied Probability and Informatics, RUDN University, Moscow, Russia

    Vladimir V. Rykov

  2. City University of Hong Kong, Hong Kong, Hong Kong

    Nozer D. Singpurwalla

  3. Steklov Mathematical Institute of Russian Academy of Sciences, Moscow, Russia

    Andrey M. Zubkov

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Grishunina, Y., Manita, L. (2017). Optimal Antivirus Protection Strategy in Computer Networks. In: Rykov, V., Singpurwalla, N., Zubkov, A. (eds) Analytical and Computational Methods in Probability Theory. ACMPT 2017. Lecture Notes in Computer Science(), vol 10684. Springer, Cham. https://doi.org/10.1007/978-3-319-71504-9_8

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  • DOI: https://doi.org/10.1007/978-3-319-71504-9_8

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71503-2

  • Online ISBN: 978-3-319-71504-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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