Advances in stochastic epidemic modeling: tackling worm transmission in wireless sensor networks

Abstract

This research investigates the security challenges posed by worm propagation in wireless sensor networks (WSNs). A novel stochastic susceptible – infectious – vaccination – recovered model is introduced to analyse the dynamics of worm spread. Conditions for the existence of a unique global solution are examined, and necessary conditions for worm eradication are established. By incorporating random environmental fluctuations, the proposed model provides a more precise depiction of propagation dynamics than deterministic models. Empirical findings are presented to validate the model’s predictive accuracy across diverse scenarios, underscoring its robustness. Numerical simulations affirm the effectiveness of the analytical approach in understanding worm propagation within WSNs. The study offers valuable insights into worm dynamics and proposes a methodological framework to enhance network security. The findings underscore the significant role of stochastic systems in modelling and provide strategic perspectives for designing resilient defensive frameworks against worm attacks in WSNs.

Keywords

• Wireless sensor networks (WSNs)
• stochastic epidemic model
• worm propagation