LAPSE:2023.34384
Published Article
LAPSE:2023.34384
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, Igor Saenko
April 26, 2023
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, fuzzy logic algorithm, traffic decomposition
Suggested Citation
Privalov A, Lukicheva V, Kotenko I, Saenko I. Increasing the Sensitivity of the Method of Early Detection of Cyber-Attacks in Telecommunication Networks Based on Traffic Analysis by Extreme Filtering. (2023). LAPSE:2023.34384
Author Affiliations
Privalov A: Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia
Lukicheva V: Emperor Alexander I Saint-Petersburg State Transport University, 9 Moskovsky pr., St. Petersburg 190031, Russia
Kotenko I: Saint-Petersburg Institute for Informatics and Automation of Russian Academy of Sciences (SPIIRAS), 39, 14 Liniya, St. Petersburg 199178, Russia [ORCID]
Saenko I: Saint-Petersburg Institute for Informatics and Automation of Russian Academy of Sciences (SPIIRAS), 39, 14 Liniya, St. Petersburg 199178, Russia [ORCID]
Journal Name
Energies
Volume
13
Issue
11
Article Number
E2774
Year
2020
Publication Date
2020-06-01
Published Version
ISSN
1996-1073
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Original Submission
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PII: en13112774, Publication Type: Journal Article
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LAPSE:2023.34384
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doi:10.3390/en13112774
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Apr 26, 2023
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