Work place: Wrocław University of Technology, Wrocław, Poland
E-mail: Grzegorz.Kolaczek@pwr.edu.pl
Website:
Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Information Security, Network Architecture, Network Security, Data Structures and Algorithms
Biography
Grzegorz Kołaczek, born in 1973. Ph. D. and associate professor in Wroclaw University of Technology. His main research interests include computer and network security, service oriented systems, big data analysis and optimization.
By Jarosiaw Bernacki Grzegorz Koiaczek
DOI: https://doi.org/10.5815/ijcnis.2015.09.02, Pub. Date: 8 Aug. 2015
In this paper a few methods for anomaly detection in computer networks with the use of time series methods are proposed. The special interest was put on Brown's exponential smoothing, seasonal decomposition, naive forecasting and Exponential Moving Average method. The validation of the anomaly detection methods has been performed using experimental data sets and statistical analysis which has shown that proposed methods can efficiently detect unusual situations in network traffic. This means that time series methods can be successfully used to model and predict a traffic in computer networks as well as to detect some unusual or unrequired events in network traffic.
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