DDoS detection using CURE clustering algorithm with outlier removal clustering for handling outliers

DoS (Denial of Service) and DDoS (Distributed Denial of Service) is an anomalous traffic phenomena that is need serious attention. In the previous research has already been discussed on traffic anomaly detection based on clustering, with a hierarchical clustering algorithm method. In this paper, we...

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Vydáno v:	2015 International Conference on Control, Electronics, Renewable Energy and Communications (ICCEREC) s. 12 - 18
Hlavní autoři:	Laksono, Muhammad Agung Tri, Purwanto, Yudha, Novianty, Astri
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 01.08.2015
Témata:	Algorithm design and analysis Clustering algorithms Computer crime CURE clustering algorithm DDoS Intrusion detection outliers Partitioning algorithms Shape Telecommunication traffic traffic anomaly detection
On-line přístup:	Získat plný text
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Popis
Shrnutí:	DoS (Denial of Service) and DDoS (Distributed Denial of Service) is an anomalous traffic phenomena that is need serious attention. In the previous research has already been discussed on traffic anomaly detection based on clustering, with a hierarchical clustering algorithm method. In this paper, we introduce a method of network traffic anomaly (DDoS) detection using modernization of the traditional hierarchical clustering algorithm that is CURE clustering algorithm. CURE has advantages in the case of outliers. We modify the algorithm using outlier removal clustering (ORC) in terms of dealing with outliers. We apply the mechanism to detect and remove outliers from the specified clusters. We perform the outlier elimination scheme in two phase and do the removal at the point which detected as outlier. We also give an analysis and results of the proposed method.
DOI:	10.1109/ICCEREC.2015.7337029