Increasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering

Andrey Privalov, Vera Lukicheva, Igor Kotenko and Igor Saenko
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Andrey Privalov: Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia
Vera Lukicheva: Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia
Igor Kotenko: Saint-Petersburg Institute for Informatics and Automation of Russian Academy of Sciences (SPIIRAS), 39, 14 Liniya, St. Petersburg 199178, Russia
Igor Saenko: Saint-Petersburg Institute for Informatics and Automation of Russian Academy of Sciences (SPIIRAS), 39, 14 Liniya, St. Petersburg 199178, Russia

Energies, 2020, vol. 13, issue 11, 1-18

Abstract: The paper proposes a method for improving the accuracy of early detection of cyber attacks with a small impact, in which the mathematical expectation is a fraction of the total, and the pulse repetition period is quite long. Early detection of attacks against telecommunication networks is based on traffic analysis using extreme filtering. The algorithm of fuzzy logic for deciding on the results of extreme filtering is suggested. The results of an experimental evaluation of the proposed method are presented. They demonstrate that the method is sensitive even with minor effects. In order to eliminate the redundancy of the analyzed parameters, it is enough to use the standard deviation and the correlation interval for decision making.

Keywords: detection of cyberattacks; extreme filtering; traffic decomposition; fuzzy logic algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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