W ramach prac badawczych realizowanych w obszarze zastosowań metod AI, VR i IoE w diagnostyce, nadzorowaniu i sterowaniu procesów w Przemyśle 4.0 opublikowany został artykuł w czasopiśmie Applied Sciences (obecna punktacja ministerialna: 70 pkt, Impact Factor: 2.217):
Dymora, P.; Mazurek, M. An Innovative Approach to Anomaly Detection in Communication Networks Using Multifractal Analysis. Appl. Sci. 2020, 10, 3277. https://www.mdpi.com/2076-3417/10/9/3277
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).
