Content area

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.

Details

1009240
Title
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
Volume
15
Issue
1
Pages
228
Publication year
2025
Publication date
2025
Publisher
Nature Publishing Group
Place of publication
London
Country of publication
United States
Publication subject
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
Document type
Journal Article
Publication history
 
 
Online publication date
2025-01-02
Milestone dates
2024-12-02 (Registration); 2024-07-03 (Received); 2024-12-02 (Accepted)
Publication history
 
 
   First posting date
02 Jan 2025
ProQuest document ID
3151014589
Document URL
https://www.proquest.com/scholarly-journals/novel-numerical-solution-nonlinear-stochastic/docview/3151014589/se-2?accountid=208611
Copyright
Copyright Nature Publishing Group 2025
Last updated
2025-01-03
Database
ProQuest One Academic