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Towards understanding the effectiveness of patch injection

Author

Listed:
  • Huang, Da-Wen
  • Yang, Lu-Xing
  • Yang, Xiaofan
  • Wu, Yingbo
  • Tang, Yuan Yan

Abstract

To contain the prevalence of computer virus on a network, we have to continuously inject new patches into the network. As the limited communication bandwidth restricts the patch injection rate, we need to evaluate the performance of a patch injection rate in restraining computer infections. This paper focuses on the performance evaluation problem. We propose a virus–patch interacting model with patch injection mechanism, and show that this model admits a globally stable equilibrium. This result implies that the fraction of infected nodes will approach a common value. Therefore, we recommend the asymptotic fraction of infected nodes to serve as a measure of performance of the associated patch injection rate. We also examine the influence of different parameters on the asymptotic fraction of infected nodes. In particular, we find that patch injection is particularly effective for densely connected networks. This work takes the first step towards understanding the effectiveness of patch injection.

Suggested Citation

  • Huang, Da-Wen & Yang, Lu-Xing & Yang, Xiaofan & Wu, Yingbo & Tang, Yuan Yan, 2019. "Towards understanding the effectiveness of patch injection," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 526(C).
    • Handle: RePEc:eee:phsmap:v:526:y:2019:i:c:s0378437119305527
    DOI: 10.1016/j.physa.2019.04.192
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    Cited by:

    1. Guiyun Liu & Jieyong Chen & Zhongwei Liang & Zhimin Peng & Junqiang Li, 2021. "Dynamical Analysis and Optimal Control for a SEIR Model Based on Virus Mutation in WSNs," Mathematics, MDPI, vol. 9(9), pages 1-16, April.

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