Open AccessModeling Worm Proliferation in Wireless Sensor Networks with Discrete Fractional Order System
Author(s) -
A. George Maria Selvam,
S. Godfrey Winster,
R. Janagaraj,
G. Maria Jones
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.e4594.018520
Subject(s) - basic reproduction number , node (physics) , stability theory , wireless sensor network , stability (learning theory) , reproduction , computer science , consistency (knowledge bases) , order (exchange) , radius , mathematics , computer network , physics , artificial intelligence , ecology , biology , economics , population , demography , finance , quantum mechanics , nonlinear system , machine learning , sociology
Wireless sensor networks (WSNs) are at risk to cyber attacks and thus security is of vital concern. WSN is a soft target for worm attacks due to fragile defence mechanism in the network . A single unsecured node can essentially propogate the worm in the complete network via communication. Mathematical epidemic models are useful in the study of propagation of worms in WSNs. This work considers a fractional order discrete model of attacking and spreading dynamics of worms in WSNs of the form The proposed epidemic model is probed with the assistance of stability theory. Basic reproduction number (R0)is determined for the analysis of the dynamics of worm propagation in WSNs. The equilibrium states are computed and analyzed the stability. Basic reproduction number R0 enables to discover the threshold values for communication radius and node density distribution. If reproduction number is less than one, the worm free equilibrium state (WFE) is locally asymptotically stable (LAS) and if reproduction number is more than one then the endemic equilibrium state (EE) is asymptotically stable. Numerical illustrations affirm the consistency of the theoretical analysis and stimulating dynamical behavior of the system is observed.