Dynamical Modeling and Analysis of Worm Propagation in Networks

It is very important to study the model of worm propagation and analyze its dynamic evolution for understanding and mitigating network security threats. In this paper, considering network heterogeneity and two ways of worm propagation: scanning IP addresses and network‐sharing propagation, we develop a new model to study the dynamics of worm propagation. Based on the proposed model, we conduct the theoretical analysis and prove that if the basic reproduction number is less than 1, the worm‐free equilibrium is globally asymptotically stable. Then, the final size is given, and data fitting is carried out by using the actual monitoring data. Finally, we examine the effect of model parameters on the basic reproduction number and analyze the changes of infected nodes in different cases. Numerical experiments show the rationality of the established model. The results indicate that, among the two ways of worm propagation, the network‐sharing propagation facilitates more rapid dissemination of the worm.

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Publication Details

Journal
Discrete Dynamics in Nature and Society
Published
2026-01-01
DOI
https://doi.org/10.1155/ddns/5702228
Primary Topic
Network Security and Intrusion Detection
Type
article
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article

Dynamical Modeling and Analysis of Worm Propagation in Networks

Shujuan Zhang, Yihong Li
Discrete Dynamics in Nature and Society
Network Security and Intrusion Detection
article

Dynamical Modeling and Analysis of Worm Propagation in Networks

Shujuan Zhang, Yihong Li
article en

Abstract

It is very important to study the model of worm propagation and analyze its dynamic evolution for understanding and mitigating network security threats. In this paper, considering network heterogeneity and two ways of worm propagation: scanning IP addresses and network‐sharing propagation, we develop a new model to study the dynamics of worm propagation. Based on the proposed model, we conduct the theoretical analysis and prove that if the basic reproduction number is less than 1, the worm‐free equilibrium is globally asymptotically stable. Then, the final size is given, and data fitting is carried out by using the actual monitoring data. Finally, we examine the effect of model parameters on the basic reproduction number and analyze the changes of infected nodes in different cases. Numerical experiments show the rationality of the established model. The results indicate that, among the two ways of worm propagation, the network‐sharing propagation facilitates more rapid dissemination of the worm.

Discrete Dynamics in Nature and SocietyVol. 2026(1)
North University of China (CN)
Openalex Percentile: Top 95%
Network Security and Intrusion Detection
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