Segmentation of data when analyzing the state of telecommunication systems
Lebedev I. Rzayev B.
March 2023Institute of Advanced Engineering and Science
Indonesian Journal of Electrical Engineering and Computer Science
2023#29Issue 31473 - 1479 pp.
The identification of abnormal situations in information and telecommunication systems is considered, based on analyze statistical information of network traffic packages. The method of identifying an anomalous situation based on segmentation of data sample is proposed. The method is aimed at using classifying algorithms that have the best quality indicators on individual data segments. The proposed method will be useful for monitoring information security systems. The method registers of factors that affect the change in the properties of targeted variables. Impact detection allows you to generate data samples, depending on current and expected situations. On the example of the NSL-KDD dataset, there was a division of many data into subset, taking into account the influence of the factors on the range of values. The processing of factors is shown using the change point detection function in the time series. With its use, a division of data sample by the final number of non-intersecting measurable subsets has been made. The results of Accuracy, Precision, F-Measure, Recall for various classifiers are shown. The proposed method allows to increase the quality indicators of classification in continuously changing operating conditions of telecommunication systems.
Change point detection , Influencing factors , Information security , Network traffic , Segmentation
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Laboratory of Intelligent Systems, Saint Petersburg Federal Research Center of the RAS, Saint Petersburg, Russian Federation
Department of Information Systems, Faculty of Computer Systems and Vocational Education, S. Seifullin Kazakh Agrotechnical University, Astana, Kazakhstan
Laboratory of Intelligent Systems
Department of Information Systems
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