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Reseach Article

Malicious Objects Propagation Dynamics in the Network

Published on None 2011 by Dinesh Kumar Saini
Evolution in Networks and Computer Communications
Foundation of Computer Science USA
ENCC - Number 1
None 2011
Authors: Dinesh Kumar Saini
5013fd0b-63b6-4e0e-8ba7-52c42b509fee

Dinesh Kumar Saini . Malicious Objects Propagation Dynamics in the Network. Evolution in Networks and Computer Communications. ENCC, 1 (None 2011), 44-51.

@article{
author = { Dinesh Kumar Saini },
title = { Malicious Objects Propagation Dynamics in the Network },
journal = { Evolution in Networks and Computer Communications },
issue_date = { None 2011 },
volume = { ENCC },
number = { 1 },
month = { None },
year = { 2011 },
issn = 0975-8887,
pages = { 44-51 },
numpages = 8,
url = { /specialissues/encc/number1/3719-encc008/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Evolution in Networks and Computer Communications
%A Dinesh Kumar Saini
%T Malicious Objects Propagation Dynamics in the Network
%J Evolution in Networks and Computer Communications
%@ 0975-8887
%V ENCC
%N 1
%P 44-51
%D 2011
%I International Journal of Computer Applications
Abstract

The network world is enormous, dynamic, divers and incredibly very high complex. Survival of computer network is highly depended on the capability of the network to fight with malicious objects which are abundantly available in the cyber space. Our network world is growing larger in size and ways of networking like wired and wireless with different techniques are also growing, but reliability and robustness is the issue of concern in the today’s network. In this paper biologically based mathematical inspired modelling is carried out to monitor the spread of these malicious objects in the network. An attempt is made to develop a discrete-time “Susceptible -Attacked-Infectious-Non-Infectious (SAIN)” model for computer infection with the aim of estimating parameters such as time of attack, incubation time, and mean infection time by using probabilistic approach. SAIN model is basically compartment-specific approach; each compartment is having distinct boundaries. Computer nodes transfers from one compartment to other such as Susceptible to Attacked, Attacked to Infectious, and Infectious to Non-Infectious with some stochastic random variable. In the end of the paper it is described where and how to use this mathematical modelling for designing the cyber defence systems.

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Index Terms

Computer Science
Information Sciences

Keywords

Malicious Object propagation Mathematical Modelling