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A hybrid strategy for network immunization

Author

Listed:
  • Li, Xianghua
  • Guo, Jingyi
  • Gao, Chao
  • Zhang, Leyan
  • Zhang, Zili

Abstract

Network immunization is an effective strategy for restraining virus spreading in computer networks and rumor propagation in social networks. Currently, lots of strategies are proposed based on topological structures of networks, such as degree-based and betweenness-based network immunization strategies. However, these studies assume that nodes in a network are homogeneous, i.e., each node has the same characteristic. However, more and more studies have revealed the heterogeneous characteristic of a network. For example, the activities of individual in a computer and social network play an important role in virus spreading and rumor propagation. Some active individuals can promote the outbreak of virus and the spread of a rumor. In this paper, a new network immunization strategy is proposed through combining the characteristics of network structure with node activities. Comprehensive experiments in both benchmark and synthetic networks show that our proposed strategy can restrain virus prorogation effectively.

Suggested Citation

  • Li, Xianghua & Guo, Jingyi & Gao, Chao & Zhang, Leyan & Zhang, Zili, 2018. "A hybrid strategy for network immunization," Chaos, Solitons & Fractals, Elsevier, vol. 106(C), pages 214-219.
    • Handle: RePEc:eee:chsofr:v:106:y:2018:i:c:p:214-219
    DOI: 10.1016/j.chaos.2017.11.029
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    References listed on IDEAS

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    Cited by:

    1. Li, Jingwei & Li, Shouwei, 2023. "Immunization of systemic risk in trade–investment networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    2. Su, Zhen & Liu, Fanzhen & Gao, Chao & Gao, Shupeng & Li, Xianghua, 2018. "Inferring infection rate based on observations in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 107(C), pages 170-176.
    3. Li, Ai-Wen & Xu, Xiao-Ke & Fan, Ying, 2022. "Immunization strategies for false information spreading on signed social networks," Chaos, Solitons & Fractals, Elsevier, vol. 162(C).

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