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Article

An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis

by
Paweł Dymora
* and
Mirosław Mazurek
Faculty of Electrical and Computer Engineering, Rzeszów University of Technology, al. Powstańców Warszawy 12, 35-959 Rzeszów, Poland
*
Author to whom correspondence should be addressed.
Appl. Sci. 2020, 10(9), 3277; https://doi.org/10.3390/app10093277
Submission received: 11 April 2020 / Revised: 29 April 2020 / Accepted: 6 May 2020 / Published: 8 May 2020
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Abstract

Fractal and multifractal analysis can help to discover the structure of the communication system, and in particular the pattern and characteristics of traffic, in order to understand the threats better and detect anomalies in network operation. The massive increase in the amount of data transmitted by different devices makes these systems the target of various types of attacks by cybercriminals. This article presents the use of fractal analysis in detecting threats and anomalies. The issues related to the construction and functioning of the Security Operations Centre (SOC) are presented. To examine the correctness of SOC, several attacks on virtual systems located in the network were carried out, such as Denial of Service (DoS) attack, brute force, malware infections, exploits. Based on data collected from monitoring and devices, the response to the event was analyzed, and multifractal spectra of network traffic before and during the incident were created. The collected information allows us to verify the theses and confirm the effectiveness of multifractal methods in detecting anomalies in the operation of any Information and Communication Technology (ICT) network. Such solutions will contribute to the development of advanced intrusion detection systems (IDS).
Keywords: anomaly detection; computer network traffic; Hurst exponent; multifractal spectrums; TCP/IP; IoT; communication security; Industry 4.0; Security Operation Center (SOC) anomaly detection; computer network traffic; Hurst exponent; multifractal spectrums; TCP/IP; IoT; communication security; Industry 4.0; Security Operation Center (SOC)

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MDPI and ACS Style

Dymora, P.; Mazurek, M. An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis. Appl. Sci. 2020, 10, 3277. https://doi.org/10.3390/app10093277

AMA Style

Dymora P, Mazurek M. An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis. Applied Sciences. 2020; 10(9):3277. https://doi.org/10.3390/app10093277

Chicago/Turabian Style

Dymora, Paweł, and Mirosław Mazurek. 2020. "An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis" Applied Sciences 10, no. 9: 3277. https://doi.org/10.3390/app10093277

APA Style

Dymora, P., & Mazurek, M. (2020). An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis. Applied Sciences, 10(9), 3277. https://doi.org/10.3390/app10093277

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