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Modeling and Hopf Bifurcation Analysis of Benign Worms with Quarantine Strategy

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Cyberspace Safety and Security (CSS 2017)

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Abstract

Since the Morris worm occurred in 1988, malwares have threatened the network persistently. With rapid development of the Internet, network security issues become increasingly serious. Recently, the benign worms become a new active countermeasure to deal with the worm threat. In this paper, we propose a compositive-hybrid benign worm propagation model with quarantine strategy. Usually, quarantine strategy will lead to a time delay, and the worm propagation system will be unstable and out of control with the time delay increases. Then the existence condition and the stability of the positive equilibrium are derived. Through our derivation and analysis, the threshold \( \tau_{0} \) of Hopf bifurcation is obtained. The system will be stable when time delay \( \tau < \tau_{0} \). In addition, numerical experiments are performed and the effect of benign worms is displayed by comparing with the model that do not include benign worms. Furthermore, simulation experiments are carried out to verify our conclusions.

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References

  1. Moore, D., Shannon, C., Claffy, K.: Code-Red: a case study on the spread and victims of an internet worm. In: ACM SIGCOMM Workshop on Internet Measurement 2002, pp. 273–284, Marseille, France, November 2002. doi:10.1145/637201.637244

  2. EEye Digital Security. Code Red worm (2001). http://www.eeye.com/html/research/advisories/al20010717.html

  3. eEye Digital Security, ANALYSIS: CodeRed II Worm. http://www.eeye.com/html/Research/Advisories/AL20010804.html

  4. Moore, D., Paxson, V., Savage, S., Shannon, C., Staniford, S., Weaver, N.: Inside the slammer worm. IEEE Mag. Secur. Privacy 1(4), 33–39 (2003). doi:10.1109/MSECP.2003.1219056

    Article  Google Scholar 

  5. Weaver, N., Staniford, S., Paxson, V.: Very fast containment of scanning worms. In: Conference on Usenix Security Symposium, vol. 13, p. 3. USENIX Association (2004). doi:https://doi.org/10.1007/978-0-387-44599-1_6

  6. Schechter, S.E., Jung, J., Berger, A.W.: Fast detection of scanning worm infections. In: Jonsson, E., Valdes, A., Almgren, M. (eds.) RAID 2004. LNCS, vol. 3224, pp. 59–81. Springer, Heidelberg (2004). doi:10.1007/978-3-540-30143-1_4

    Chapter  Google Scholar 

  7. Kim, H.A., Karp, B.: Autograph: toward automated, distributed worm signature detection. In: USENIX Security Symposium, August 9–13, 2004, San Diego, CA, USA, pp. 271–286. DBLP (2004)

    Google Scholar 

  8. Lloyd, A.L., May, R.M.: Epidemiology. How viruses spread among computers and people. Science 292(5520), 1316 (2001). doi:10.1126/science.1061076

    Article  Google Scholar 

  9. Staniford, S., Paxson, V., Weaver, N.: How to own the internet in your spare time. In: USENIX Security Symposium, (pp. 149–167). USENIX Association (2002)

    Google Scholar 

  10. Streftaris, G., Gibson, G.J.: Statistical inference for stochastic epidemic models. In: Proceedings of the 17th International Workshop on Statistical Modeling, Chania, UK, pp. 609–616 (2002)

    Google Scholar 

  11. Martin, J.C., Burge III, L.L., Gill, J.I., Washington, A.N., Alfred, M.: Modelling the spread of mobile malware. Int. J. Comput. Aided Eng. Technol. 2(1), 3–14 (2010). doi:10.1504/IJCAET.2010.029592

  12. Frauenthal, J.C.: Mathematical Modeling in Epidemiology, pp. 115–123. Springer, New York (1980)

    Book  MATH  Google Scholar 

  13. Zhou, H., Wen, Y., Zhao, H.: Modeling and analysis of active benign worms and hybrid benign worms containing the spread of worms. In: International Conference on Networking, p. 65. IEEE (2007). doi:http://doi.ieeecomputersociety.org/10.1109/ICN.2007.58

  14. Dong, T., Liao, X., Li, H.: Stability and Hopf bifurcation in a computer virus model with multistate antivirus. Abstract Appl. Anal. 2012(2), 374–388 (2012). doi:10.1155/2012/841987

    MATH  MathSciNet  Google Scholar 

  15. Yao, Y., Xie, X.W., Guo, H., et al.: Hopf bifurcation in an Internet worm propagation model with time delay in quarantine. Math. Comput. Model. 57(11–12), 2635–2646 (2013). doi:10.1016/j.mcm.2011.06.044

    Article  MATH  MathSciNet  Google Scholar 

  16. Castaneda, F., Sezer, E.C., Xu, J.: WORM vs. WORM: preliminary study of an active counter-attack mechanism. In: ACM Workshop on Rapid Malcode, Worm 2004, Washington, DC, USA, pp. 83–93, October 2004. doi:10.1145/1029618.1029631

  17. Yang, Y., Fang, Y., Li, L.Y.: The analysis of propagation model for internet worm based on active vaccination. IEEE (2008). doi:10.1109/ICNC.2008.431

  18. Hassard, B., Kazarino, D., Wan, Y.: Theory and Application of Hopf Bifurcation. Cambridge University Press, Cambridge (1981)

    Google Scholar 

  19. Zou, C.C., Gong, W., Towsley, D.: Worm propagation modeling and analysis under dynamic quarantine defense. In: ACM Workshop on Rapid Malcode, vol. 23, pp. 51–60. ACM (2003) doi:10.1145/948187.948197

  20. Zhang, J.F., Li, W.T., Yan, X.P.: Hopf bifurcation and stability of periodic solutions in a delayed eco-epidemiological system. Appl. Math. Comput. 198(2), 865–876 (2008). doi:10.1016/j.amc.2007.09.045

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Acknowledgments

This paper is supported by Program for Fundamental Research Funds of the Central Universities under Grant no. N150402006 and N161704005.

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Correspondence to Yu Yao or Qiang Fu .

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Yao, Y., Fu, Q., Sheng, C., Yang, W. (2017). Modeling and Hopf Bifurcation Analysis of Benign Worms with Quarantine Strategy. In: Wen, S., Wu, W., Castiglione, A. (eds) Cyberspace Safety and Security. CSS 2017. Lecture Notes in Computer Science(), vol 10581. Springer, Cham. https://doi.org/10.1007/978-3-319-69471-9_24

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  • DOI: https://doi.org/10.1007/978-3-319-69471-9_24

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