A METHOD FOR SYNTHESIZING HARDWARE AND SOFTWARE TOOLS TO ENSURE THE STABILITY OF A CORPORATE COMPUTER NETWORK

Abstract

The paper represents a method for ensuring the resilience of a corporate computer network under the influence of various types of threats. This article will provide an overview of the aspects of resilience and existing approaches to ensuring resilient routing. This article is the result of many studies and experiments, and evaluating the final result, it can be noted that this method can successfully reflect the possible importance of a node when it comes to epidemic dynamics for various network models to ensure network resilience. A possible way to solve the problem was to use the theory of linear stationary systems and the phenomenon of propagation in networks as the basis of the method. Complex interdependencies between their elements characterize various systems. The method of synthesizing hardware and software means of ensuring the stability of a corporate computer network consists of such steps as representing networks as a linear stationary system, modelling the stability of a computer network in the context of epidemics by using virtual network expansion, studying the stability of a computer network in the context of uncertain data transmission and virtual network expansion, processing input data received from the modelled computer network, etc. To solve the problem, the method involves the theory of linear stationary systems and the use of the NiR metric, which can successfully reflect the possible importance of a node when it comes to the dynamics of an epidemic for various network models to ensure network resilience. The method is tested by simulations, the results of which show a high correlation with the actual propagation dynamics modeled by SI and SIR processes. NiR also shows a small variance, which means it is reliable for different computer network topologies. The method also involves finding the most critical nodes in a computer network, for which a cascading failure model was used, which models overloaded nodes as non-functional.