Bimal Kumar Mishra

Work place: Department of Applied Mathematics, Birla Institute of Technology, Mesra, Ranchi-835215, India



Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Data Structures and Algorithms, Analysis of Algorithms, Mathematics of Computing


Bimal Kumar Mishra, born in 1969. Professor and Ph.D. supervisor in BIT Mesra, Ranchi. His main research interests include: Mathematical models on Cyber attack, defense and crime; Infectious disease; Nonlinear dynamics.

Author Articles
Transmission Dynamics of Malware in Networks Using Caputo Fractional Order Derivative

By Jyoti Kumari Gupta Bimal Kumar Mishra

DOI:, Pub. Date: 8 Jun. 2024

Fractional calculus plays a crucial role in the representation of various natural and physical phenomena by incorporating the inherent non-locality and long-term memory effect of fractional operators. These models offer a more precise and systematic depiction of the underlying phenomena. The focus of this research paper is on the utilization of fractional calculus in the context of the epidemic model. Specifically, the model considers a fractional order ρ, where 0<ρ≤1, and employs the Caputo fractional order derivative to describe the transmission of malware in both wireless and wired networks. The basic reproduction number, along with the fractional order ρ, is identified as the threshold parameter in this model. The stability of the system is analysed at different stages of the reproduction number, considering both local and global asymptotic stability. Additionally, sensitivity analysis is conducted on the model parameters to determine the direction of change in the reproduction number. This analysis aids in understanding whether the reproduction number will increase or decrease under different scenarios. To obtain numerical results, the Fractional Forward Euler Method is utilized for simulation purposes. This method enables the computation of the model's dynamics and offers insights into the behaviour of the system. While the Caputo fractional order derivative offers a promising framework for modelling epidemic dynamics, they often entail significant computational overhead, limiting the scalability and practical utility of fractional calculus-based epidemic models, especially in real-time simulation and forecasting scenarios.

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