Network Traffic Classification for Anomaly Detection: Fuzzy Clustering Based Approach

2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD) 2015
Jūlija Asmuss, Gunārs Lauks

In this paper we develop network traffic classification and anomaly detection methods based on traffic time series analysis using fuzzy clustering technique. The effectiveness of fuzzy and possibilistic algorithms is compared on generated traffic data with and without traffic attack components.

Keywords
traffic classification; anomaly detection; fuzzy clustering; validity indices
DOI
10.1109/FSKD.2015.7381960

Asmuss, J., Lauks, G. Network Traffic Classification for Anomaly Detection: Fuzzy Clustering Based Approach. In: 2015 12th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), China, Zhangjiajie, 15-17 August, 2015. Piscataway, NJ: IEEE, 2015, pp.313-318. ISBN 978-1-4673-7681-5. e-ISBN 978-1-4673-7682-2. Available from: doi:10.1109/FSKD.2015.7381960

Publication language
English (en)