A.A. Sychugov – Ph.D.(Eng.), Associate Professor, 

Head of Department «Information Security», Tula State University

E-mail: xru2003@list.ru

A.P. Anchishkin – Student, 

Department «Information Security», Tula State University

E-mail: alexan999@yandex.ru

D.V. Chernov – Assistant, 

Department «Information Security», Tula State University; Head of the Information Security Sector, JSC ADC (Tula) E-mail: cherncib@gmail.com

The purpose of the work is a formalized description of the methodology for determining the list of current threats to information security, the implementation of which can lead to a violation of the normal operation of multi-level distributed automated process control systems, as well as a set of information security measures required to minimize the risks of the implementation of current threats. This necessitates the development of new effective solutions. The article describes the method of analysis of the state of technological processes as part of the monitoring system, based on the method of single-class classification OneClass SVM. The existing methods of analysis of the state of technological processes are considered. The most effective were the methods of machine learning, which showed a high percentage of accuracy. On the basis of known models of technological processes, a new model of technological process, not previously found in open sources, is proposed as an infinite data flow with changing properties with a large number of parameters. An experiment is described in which the effectiveness of the proposed method is studied and its results are presented. Its solvency is shown, it is noted that it can be used in modern systems of monitoring the state of technological processes to identify malfunctions and threats to information security.

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