Abstract
Background & Objective: The wireless sensor networks (WSNs) have forthcoming constraints due to which there are serious security issues.
Methods: In this paper, we study the dynamics of worm propagation in Wireless Sensor Networks is based on epidemic theory. The proposed model demonstrates the effect of quarantined and recovery state on worms propagation in WSNs. This model consists of the different state of epidemics are as Susceptible- Exposed- Infected- Quarantined- Recovered (SEIQR). The Basic Reproduction Number (R0) is a critical value for the study of worm propagation dynamics in WSNs. If the value of is less than or equal to one the worm-free equilibrium is globally asymptotically stable, and if is greater than one the worm will exist in the network. This model enlightens the propagation and controlling mechanism process of worm propagation. Derived the expression for communication radius and the node density and find the relationship with the performance of wireless communication system is studied by changing the parameters. Control mechanism and performance of the proposed model is validated through extensive simulation results.
Results and Discussion: Consequently, the analysis confirms improvement in the vital aspects (energy efficiency, transmission efficiency, network reliability) for any wireless sensor network.
Conclusion: The SEIQR model provides an advanced mechanism to control worms’ propagation as compared to the existing model.
Keywords: Epidemic model, malicious code, wireless sensor network, basic reproduction number, control mechanism, infectious nodes.
Graphical Abstract
Related Journals
Recent Advances in Computer Science and Communications
Related Books
Challenges and Opportunities for Deep Learning Applications in Industry 4.0
Recent Advances in IoT and Blockchain Technology
Augmented Intelligence: Deep Learning, Machine Learning, Cognitive Computing, Educational Data Mining
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments Part II
Machine Learning and Its Application: A Quick Guide for Beginners
Computational Intelligence For Data Analysis
Applied Machine Learning and Multi-Criteria Decision-Making in Healthcare
Advanced Computing Techniques: Implementation, Informatics and Emerging Technologies
How to Design Optimization Algorithms by Applying Natural Behavioral Patterns
Human-Computer Interaction and Beyond: Advances Towards Smart and Interconnected Environments (Part I)
26
3