Modeling and Analysis of Antimalware Effect on Wireless Sensor Network

Wireless Sensor Network (WSN) suffers critical challenge against malware attack due to resource constraints. One compromised node is enough to spread malware in the whole network. A mathematical model namely Susceptible-Exposed-Infectious-Antimalware-Recovered(SEIAR) is proposed. The concept of epidemic modeling has been used for the study of proposed model. The basic reproduction number of model is obtained, that determines the global and local propagation dynamics of malware in the WSN. Stability conditions and equilibrium points of the model have been obtained. It achieves improved protection technique against malware attacks and enhances the lifetime of WSN. The proposed model provides better recovery mechanism against malware attack in WSN. The simulation outcomes verify that the proposed scheme is efficient. Finally, an epidemic model.