Markov Model of Unsteady Profile of Normal Behavior of Network Objects of Computer Systems

Ackoski, Jugoslav (2019) Markov Model of Unsteady Profile of Normal Behavior of Network Objects of Computer Systems. In: CMiGIN 2019, 29 Nov 2019, Lviv, Ukraine.

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Abstract

The article is devoted to the ongoing scientific and applied issue on improvement of systems of detection of cyberattacks on net- work objects of computer systems. Detection systems are considered based on determining the tolerance of deviations of the current values of the controlled functional parameters of the computer system from the profiles of normal behavior. It is established that one of the main disad- vantages of network cyberattack detection systems is the imperfection of normal behavior profiles, which are insufficiently adapted to the typ- ical non-stationary nature of the dynamics of the controlled functional parameters. It is proposed to form non-stationary profiles of normal be- havior of network objects of computer systems on the basis of multipe- riodic Markov model, which allows to take into account the typical na- ture of the dynamics of functional parameters that reflect the state of se- curity of network objects of computer systems. The peculiarity of the model is the modeling of each of the stationary sections of the dynamics of the functional parameter using a homogeneous Markov chain with successive transitions. It is experimentally established that the applica- tion of the developed multiperiodic model allows to increase the accu- racy of forecasting the dynamics of functional parameters up to 2 times. Moreover, it is shown that the prospects for further research are associ- ated with the development of methods for applying the solutions of the theory of spectral analysis of data to determine the significant periods of the process of changing functional parameters.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Natural sciences > Computer and information sciences
Divisions:	Military Academy
Depositing User:	Jugoslav Ackoski
Date Deposited:	20 Jun 2022 08:27
Last Modified:	20 Jun 2022 08:27
URI:	https://eprints.ugd.edu.mk/id/eprint/29843

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