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Behavioral Modeling of Malicious Objects in a Highly Infected Network Under Quarantine Defence
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Author(s): Yerra Shankar Rao (Gandhi Institute of Excellent Technocrafts, Deuliapatna, India), Prasant Kumar Nayak (C. V. Raman College of Engineering, Mahura, India), Hemraj Saini (Jayppe University of Information Technology, Waknaghat, India)and Tarini Charana Panda (Department of Mathematics, Ravenshaw University, Cuttack, India)
Copyright: 2019
Volume: 13
Issue: 1
Pages: 13
Source title:
International Journal of Information Security and Privacy (IJISP)
Editor(s)-in-Chief: Yassine Maleh (Sultan Moulay Slimane University, Morocco)and Ahmed A. Abd El-Latif (Menoufia University, Egypt)
DOI: 10.4018/IJISP.2019010102
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Abstract
This article describes a highly infected e-epidemic model in a computer network. This article establishes the Basic reproduction number R0, which explicitly brings out the stability conditions. Further, the article shows that if R0< 1 then the infected nodes ceases the spreading of malicious code in computer network as it dies down and consequently establishes the asymptotically stable, when R0> 1, the alternative aspect is that infected nodes stretch out into the network and becomes asymptotically unstable. The pivotal, impact of quarantine node on e-epidemic models has been verified along with its control strategy for a high infected computer network. In the MATLAB simulation, the quarantine class shows its explicit relationship with respect to high as well as low infected class, exposed class, and finally, with recovery class in order to yield increasing safety measures on transmission of malicious codes.
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