Analysis of Impact of The Charging on Propogation Dynamics of Malware in Rechargeable Wireless Sensor Networks

With the introduction of technologies like industry 4.0 and the Internet of Things, the spread of malicious software in Wireless Sensor Networks (WSN) has attracted a lot of interest from academics and industry recently. Because of these constraints, WSN which are made up of sensor nodes with limited resources face significant difficulties in maintaining security. Malware attacks, which include viruses, worms, malicious signals, and Trojan horses, are among the many security issues related to WSN that stand out as serious hazards. Malware attacks increase the energy consumption of sensor nodes while also compromising WSN security. Malware attacks usually start at a sensor node and propagate to nearby nodes throughout the network. Such attacks lead to communication disruption and information theft in addition to compromising the integrity of WSN. Because of this, protecting WSN security becomes crucial. Because malware propagation is dynamic, studying its dynamics requires the application of epidemic models. The SCILRD epidemic model, which includes the states susceptible, carrier, infectious, low energy, recovered, and dead, is presented in this study. The impact of low-energy and carrier nodes on the dynamics of malware transmission in WSN is examined by the model. Determining the proposed model's basic reproduction number is helpful in determining the stability of the system in different scenarios. The system's global and local equilibriums have been calculated. The model also looks at how charging affects malware spread in WSN. Comprehensive simulations are used to validate the mathematical results.