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Analyzing TCP Traffic Patterns Using Self Organizing Maps

9 years 6 months ago
Analyzing TCP Traffic Patterns Using Self Organizing Maps
The continuous evolution of the attacks against computer networks has given renewed strength to research on anomaly based Intrusion Detection Systems, capable of automatically detecting anomalous deviations in the behavior of a computer system. While data mining and learning techniques have been successfully applied in host-based intrusion detection, network-based applications are more difficult, for a variety of reasons, the first being the curse of dimensionality. We have proposed a novel architecture which implements a network-based anomaly detection system using unsupervised learning algorithms. In this paper we describe how the pattern recognition features of a Self Organizing Map algorithm can be used for Intrusion Detection purposes on the payload of TCP network packets.
Stefano Zanero
Added 08 Dec 2009
Updated 08 Dec 2009
Type Conference
Year 2005
Where ICIAP
Authors Stefano Zanero
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