Work place: Principal Markham College of Commerce, Hazaribag – 825301, Jharkhand, India.
E-mail: drbimalmishra@gmail.com
Website: https://scholar.google.ca/citations?user=6lukGLYAAAAJ&hl=en
Research Interests: Mathematical Analysis, Analysis of Algorithms, Computer systems and computational processes
Biography
Bimal Kumar Mishra was born in Matwari, Hazaribag, India in 1969. He received the M.Sc. degree in Operational Research and M.Sc. in Mathematics from University of Delhi, Delhi. He received his Ph.D. in 1997 from Vinoba Bhave University, Hazaribag, India and D.SC. in 2007 from Berhampur University, Odisha, India. From 2001 to 2007 he worked as a faculty member at BITS, Pilani, India and from 2007 to 2017 at BIT, Mesra, Ranchi, India as a Professor and Head, Department of Mathematics. Currently he is a Principal at Markham College of Commerce, Hazaribag. His research interests includes nonlinear dynamics and very specifically developing mathematical models on cyber attack/defense/crime, and infectious diseases. He has published more than 130 research papers in international journals of repute. He has supervised around 20 Ph.D students.
By Bimal Kumar Mishra Indu Tyagi
DOI: https://doi.org/10.5815/ijitcs.2014.03.02, Pub. Date: 8 Feb. 2014
Wireless Sensor Networks offer a powerful combination of distributed sensing, computing and communication. They lend themselves to countless applications and at the same time constrained by limited battery life, processing capability, memory and bandwidth which makes it soft target of malicious objects such as virus and worms. We study the potential threat for worm spread in wireless sensor network using epidemic theory. We propose a new model Susceptible-Exposed-Infectious-Quarantine-Recovered with Vaccination (SEIQRS-V), to characterize the dynamics of the worm spread in WSN. Threshold, equilibrium and their stability are discussed. Numerical methods are employed to solve the system of equations and MATLAB is used to simulate the system. The Quarantine is a method of isolating the most infected nodes from the network till they get recovered and the Vaccination is the mechanism to immunize the network temporarily to reduce the spread worms.
[...] Read more.By Bimal Kumar Mishra Apeksha Prajapati
DOI: https://doi.org/10.5815/ijcnis.2013.10.03, Pub. Date: 8 Aug. 2013
This paper introduces differential susceptible e-epidemic model S_i IR (susceptible class-1 for virus (S1) - susceptible class-2 for worms (S2) -susceptible class-3 for Trojan horse (S3) – infectious (I) – recovered (R)) for the transmission of malicious codes in a computer network. We derive the formula for reproduction number (R0) to study the spread of malicious codes in computer network. We show that the Infectious free equilibrium is globally asymptotically stable and endemic equilibrium is locally asymptotically sable when reproduction number is less than one. Also an analysis has been made on the effect of antivirus software in the infectious nodes. Numerical methods are employed to solve and simulate the system of equations developed.
[...] Read more.By Sounak Paul Bimal Kumar Mishra
DOI: https://doi.org/10.5815/ijcnis.2013.02.04, Pub. Date: 8 Feb. 2013
Defending against virus attacks in network is a vital part of network security. With the rapid evolution of viruses, its defense mechanism has also been evolved over the years. But given the diversity and complexity of virus propagation and its attack behavior, no defense mechanism is equipped fully to protect the network from such attacks. Several antiviruses are available in the market. But none can give full proof solution to malicious attacks in communication networks. In this paper we present a mechanism to measure and compare the relative ability of antivirus against various kinds of viruses. We construct a hierarchical structure for different virus defense mechanism. Using Analytical Hierarchy Process (AHP) we construct a pair wise comparison matrix and find the value of corresponding Eigen vectors; we then apply the theory of AHP to calculate weight of each defense index. We validated our technique with an example. Our method can provide a strong reference to design an optimal network security solution.
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