Modeling of Malware Propagation Under the Clustering Approach in Scale‐Free Networks

ABSTRACT In this paper, we present an innovative malware propagation model that combines epidemic spread and clustering techniques, specifically designed for scale‐free networks. The proposed model builds upon the susceptible–exposed–infected–recovered (SEIR) framework, effectively simulating the dissemination of malware across the network. Our research demonstrates a notable reduction in the rate of malware transmission compared to the traditional SEIR model, with this improvement in containment being attributed to the incorporation of clustering methodologies. We also calculate the basic reproduction ratio ( R 0 ) for the proposed model, which offers valuable insights into the potential consequences of malware outbreaks within the network. By exploring variations in key parameters, we deepen our understanding of the model's behavior under different conditions. Furthermore, we evaluate the role of clustering in mitigating malware spread, highlighting its significant effectiveness in reducing the overall impact of infections.