Title :
Network traffic classification for anomaly detection fuzzy clustering based approach
Author :
Julija Asmuss;Gunars Lauks
Author_Institution :
Institute of Telecommunication, Riga Technical University, Latvia
Abstract :
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 :
"Transforms","Time series analysis","Telecommunication traffic","Indexes","Clustering algorithms","Computer crime","Aggregates"
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2015 12th International Conference on
DOI :
10.1109/FSKD.2015.7381960