A novel numerical solution of nonlinear stochastic model for the propagation of malicious codes in wireless sensor networks using a high order spectral collocation technique

dc.contributor.authorZhu, Junjie
dc.contributor.authorUllah, Misbah
dc.contributor.authorUllah, Saif
dc.contributor.authorRiaz, Muhammad Bilal
dc.contributor.authorSaqib, Abdul Baseer
dc.contributor.authorAlamri, Atif M.
dc.contributor.authorAlqahtani, Salman A.
dc.date.accessioned2026-05-12T07:25:46Z
dc.date.available2026-05-12T07:25:46Z
dc.date.issued2025
dc.description.abstractThe open nature of Wireless Sensor Networks (WSNs) renders them an easy target to malicious code propagation, posing a significant and persistent threat to their security. Various mathematical models have been studied in recent literature for understanding the dynamics and control of the propagation of malicious codes in WSNs. However, due to the inherent randomness and uncertainty present in WSNs, stochastic modeling approach is essential for a comprehensive understanding of the propagation of malicious codes in WSNs. In this paper, we formulate a general stochastic compartmental model for analyzing the dynamics of malicious code distribution in WSNs and suggest its possible control. We incorporate the stochasticity in the classical deterministic model for the inherent unpredictability in code propagation, which results in a more appropriate representation of the dynamics. A basic theoretical analysis including the stability results of the model with randomness is carried out. Moreover, a higher-order spectral collocation technique is applied for the numerical solution of the proposed stochastic model. The accuracy and numerical stability of the model is presented. Finally, a comprehensive simulation is depicted to verify theoretical results and depict the impact of parameters on the model's dynamic behavior. This study incorporates stochasticity in a deterministic model of malicious codes spread in WSNs with the implementation of spectral numerical scheme which helps to capture these networks' inherent uncertainties and complex nature.
dc.description.firstpageart. no. 228
dc.description.issue1
dc.description.sourceWeb of Science
dc.description.volume15
dc.identifier.citationScientific Reports. 2025, vol. 15, issue 1, art. no. 228.
dc.identifier.doi10.1038/s41598-024-82033-2
dc.identifier.issn2045-2322
dc.identifier.urihttp://hdl.handle.net/10084/158585
dc.identifier.wos001390050200006
dc.language.isoen
dc.publisherSpringer Nature
dc.relation.ispartofseriesScientific Reports
dc.relation.urihttps://doi.org/10.1038/s41598-024-82033-2
dc.rights© The Author(s) 2024
dc.rights.accessopenAccess
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectspectral collocation technique
dc.subjectstochastic compartmental modeling
dc.subjectdistribution density
dc.subjectwireless sensor network
dc.subjectmalicious code propagation
dc.subjectstability analysis
dc.titleA novel numerical solution of nonlinear stochastic model for the propagation of malicious codes in wireless sensor networks using a high order spectral collocation technique
dc.type.statusPeer-reviewed
dc.type.versionpublishedVersion
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