Evidence map›Paper›PMID 39747261›Full record

ArticleScientific reports2025

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.

Junjie Zhu, Misbah Ullah, Saif Ullah, Muhammad Bilal Riaz, Abdul Baseer Saqib, Atif M Alamri, Salman A AlQahtani

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Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Junjie ZhuSchool of Mathematics, Shandong University, Jinan, 250100, China.
Misbah UllahDepartment of Mathematics, City University of Science and Information Technology Peshawar, Peshawar, KPK, 25000, Pakistan.
Saif UllahDepartment of Mathematics, University of Peshawar, Peshawar, KPK, 25000, Pakistan.
Muhammad Bilal RiazIT4Innovations, VSB-Technical University of Ostrava, Ostrava, Czech Republic.
Abdul Baseer SaqibFaculty of Education, Department of Mathematics, Nangrahar University, Jalalabad, Nangrahar, Afghanistan. ab_saqib@nu.edu.af.
Atif M AlamriSoftware Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.
Salman A AlQahtaniComputer Engineering Department, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The 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.

Indexed as

Spectral collocation techniqueStochastic compartmental modeling, Distribution density, Wireless sensor network, Malicious codes propagation, Stability Analysis

Identifiers

PMID39747261
PMCPMC11697034

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