A Data Mining Framework for Building Intrusion Detection Models Based on IPv6

Authors:
Zenghui Liu;Yingxu Lai
Affiliations:
Science and Technology Engineering Faculty, Beijing Vocational College of Electronic Science, Beijing, China 100029;College of Computer Science, Beijing University of Technology, Beijing, China 100124
Venue:
ISA '09 Proceedings of the 3rd International Conference and Workshops on Advances in Information Security and Assurance
Year:
2009

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Abstract

In Intrusion Detection Systems (IDS), many intelligent information processing methods, data mining technology and so on have been applied to improve detection accuracy for IPv4 network. IPv6 will inevitably take the place of IPv4 as the next generation of the Internet Protocol. Considering the problem of the urgent requirement of IDS for IPv6 networks, we present a novel intrusion detection model, and successfully applied it into an IPv6 experimental network in our lab. Lots of experiment indicated that this model can work well for intrusion detection for IPv6 network.