Construction method of cyber attacks classifier on government information resources




information and telecommunication system, cyber attack, classifier, classification, decision trees, optimization


Dynamics of successful realizations of cyber attacks, the object of which are public information resources, demonstrates the need to improve their security. One problem that hinders the implementation of effective information security systems, such as attack detection systems, is their inability to provide reliable and timely event pattern classification of information and telecommunication systems. In research materials it is proposed an approach that enhances the efficiency of attack detection systems for government information resources by the speed criteria for the given parameters of classification accuracy. This is achieved through the introduction of CBA two-step classification scheme, based on binary grouping patterns of the system behavior. The developed construction method of cyber attacks classifier, based on decision trees and optimized flow of incoming data, can reduce the construction and operation of classification models at times and provides the performance of classification accuracy of system behavior patterns.

Author Biographies

Володимир Леонідович Бурячок, State University of Telecommunications Solomenska street, 7, Kyiv, 03110

Doctor of Technical Sciences, Senior Researcher, Head of the Department

Department of Information and cyber security

Руслан Валентинович Грищук, Zhytomyr Military Institute of the State University of Telecommunications, Prospekt Mira, 22, Zhytomyr, 10004

Doctor of Technical Sciences, Senior Researcher, Leading Researcher


Віктор Миколайович Мамарєв, State University of Telecommunications Solomenska street, 7, Kyiv, 03110

Graduate student

Department of Information and cyber security


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How to Cite

Бурячок, В. Л., Грищук, Р. В., & Мамарєв, В. М. (2015). Construction method of cyber attacks classifier on government information resources. Technology Audit and Production Reserves, 1(2(21), 38–43.



Information Technologies: Original Research