Anomaly detection using Support Vector Machine classification with k-Medoids clustering

Anomaly based Intrusion Detection System, in the recent years, has become more dependent on learning methods - specially on classifications schemes. To make the classification more accurate and effective, hybrid approaches of combining with clustering techniques are often introduced. In this paper,...

Ausführliche Beschreibung

Bibliographische Detailangaben

Hauptverfasser:	Chitrakar, R., Huang Chuanhe
Format:	Tagungsbericht
Sprache:	eng
Schlagworte:	Accuracy Anomaly Detection Classification algorithms Clustering algorithms Data mining Intrusion detection k-medoids Clustering Naïve Bayes Classification Niobium Support Vector Machine Support vector machines
Online-Zugang:	Volltext bestellen
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!