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Attack and Repair Strategies for Computer Network About Viruses

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Machine Learning for Cyber Security (ML4CS 2020)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 12486))

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Abstract

The threat of computer viruses has become an increasingly important issue, so it is necessary to improve the protection of computer networks against computer viruses. This article puts forward the idea of using the curve area method to calculate the resilience of computer networks. In addition, three factors affecting computer networks in terms of computer viruses and four repair strategies for computer networks are studied. The results show that the increased infection rate and the increase in the number of initial infected nodes will not cause the network to crash; the medial-based attacks have the greatest impact on the network; the medial-based repair strategy is better than the balanced repair strategy and has the best repair effect on the network.

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References

  1. Mishra, B.K., Jha, N.: SEIQRS model for the transmission of malicious objects in computer network. Appl. Math. Model. 34(3), 710–715 (2010)

    Article  MathSciNet  Google Scholar 

  2. Mishra, B.K., Pandey, S.K.: Dynamic model of worms with vertical transmission in computer network. Appl. Math. Comput. 217(21), 8438–8446 (2011)

    MathSciNet  MATH  Google Scholar 

  3. Mishra, B.K., Saini, D.K.: SEIRS epidemic model with delay for transmission of malicious objects in computer network. Appl. Math. Comput. 188(2), 1476–1482 (2007)

    MathSciNet  MATH  Google Scholar 

  4. Donohue, I., et al.: Navigating the complexity of ecological stability. Ecol. Lett. 19(9), 1172–1185 (2016)

    Article  Google Scholar 

  5. Jung, E., Lenhart, S., Feng, Z.: Optimal control of treatments in a two-strain tuberculosis model. Discrete Continuous Dyn. Syst. Ser. B 4, 473–482 (2002)

    Article  MathSciNet  Google Scholar 

  6. Zaman, G., Kang, Y.-H., Jung, I.-H.: Optimal treatment of an SIR epidemic model with time delay. Biosystems 1, 43–50 (2009)

    Article  Google Scholar 

  7. Ren, J.G., Yang, X.F., Zhu, Q.Y., et al.: A novel computer virus model and its dynamics. Nonlinear Anal. Real World Appl. 1, 376–384 (2012)

    Article  MathSciNet  Google Scholar 

  8. Fei, S.-U., Lin, Z.-W., Yan, M.-A.: Modeling and analysis of Internet worm propagation. J. China Univ. Posts Telecommun. 17(4), 63–68 (2010)

    Article  Google Scholar 

  9. Yuan, J.L., Yang, Z.D.: Global dynamics of an SEI model with acute and chronic stages. J. Comput. Appl. Math. 2, 465–476 (2008)

    Article  MathSciNet  Google Scholar 

  10. Gao, J., Baruch, B., Albert-László, B.: Author Correction: Universal resilience patterns in complex networks. Nature 568(7751), 5–6 (2019)

    Article  Google Scholar 

  11. Holling, C.-S.: Resilience and stability of ecological systems. Ann. Rev. Ecol. Syst. 4(1), 1–23 (1973)

    Article  Google Scholar 

  12. Fang, Y., Pedroni, N., Zio, E.: Resilience-based component importance measures for critical infrastructure network systems. IEEE Trans. Reliab. 65(2), 502–512 (2016)

    Article  Google Scholar 

  13. Barker, K., Ramirez-Marquez, J.E., Rocco, C.M.: Resilience-based network component importance measures. Reliab. Eng. Syst. Saf. 117, 89–97 (2013)

    Article  Google Scholar 

  14. Cimellaro, G.P., Reinhorn, A.M., Bruneau, M.: Framework for analytical quantification of disaster resilience. Eng. Struct. 32(11), 3639–3649 (2010)

    Article  Google Scholar 

  15. Baroud, H., et al.: Importance measures for inland waterway network resilience. Transp. Res. Part E Logist. Transp. Rev. 62, 55–67 (2014)

    Article  Google Scholar 

  16. Wang, X.: Harm and prevention of computer virus. Private Sci. Technol. 11, 91 (2015)

    Google Scholar 

  17. Fang, B., Cui, X., Wang, W.: Overview of botnets. Comput. Res. Dev. 48(08), 1315–1331 (2011)

    Google Scholar 

  18. Hu, Z., Li, X.: Contagion and bailout strategy in complex financial network. Finan. Trade Econ. 38(04), 101–114 (2017)

    Google Scholar 

  19. Daron, A., Asuman, O., Alireza, T.-S.: Systemic risk and stability in financial networks. Am. Econ. Rev. 105(2), 564–608 (2015)

    Google Scholar 

  20. Huser, A.-C.: Too interconnected to fail: a survey of the interbank networks literature. J. Netw. Theor. Finan. 1(3), 1–50 (2015)

    Google Scholar 

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Acknowledgments

The authors are highly thankful for National Key Research Program (2019YFB1706001), Industrial Internet Innovation Development Project (TC190H46B), National Natural Science Foundation of China (61773001).

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Correspondence to Sheng Hong .

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Hong, S., Wang, Y. (2020). Attack and Repair Strategies for Computer Network About Viruses. In: Chen, X., Yan, H., Yan, Q., Zhang, X. (eds) Machine Learning for Cyber Security. ML4CS 2020. Lecture Notes in Computer Science(), vol 12486. Springer, Cham. https://doi.org/10.1007/978-3-030-62223-7_43

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  • DOI: https://doi.org/10.1007/978-3-030-62223-7_43

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-62222-0

  • Online ISBN: 978-3-030-62223-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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