IoT Traffic Fractal Dimension Statistical Characteristics on the Kitsune Dataset Example
https://doi.org/10.31854/1813-324X-2023-9-5-112-119
Abstract
The paper considers a method for estimating the fractal properties of traffic, and also evaluates the statistical parameters of the fractal dimension of IoT traffic. An analysis of real traffic with attacks from the Kitsune dump and an analysis of the fractal properties of traffic in normal mode and under the influence of attacks such as SSDP Flood, Mirai, OS Scan showed that jumps in the fractal dimension of traffic when attacks occur can be used to create algorithms for detecting computer attacks in IoT networks. Studies have shown that in the case of online analysis of network traffic, when assessing the RF, preference should be given to the modified algorithm for estimating the Hurst exponent in a sliding analysis window.
About the Authors
O. Shelukhin
Moscow Technical University of Communications and Informatics
Russian Federation
Russian Federation
S. Rybakov
Moscow Technical University of Communications and Informatics
Russian Federation
Russian Federation
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Review
For citations:
Shelukhin O., Rybakov S. IoT Traffic Fractal Dimension Statistical Characteristics on the Kitsune Dataset Example. Proceedings of Telecommunication Universities. 2023;9(5):112-119. (In Russ.) https://doi.org/10.31854/1813-324X-2023-9-5-112-119
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