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

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Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 5576))

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.

Supported by Scientific Research Common Program of Beijing Municipal Commission of Education (No: KM200810005030).

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© 2009 Springer-Verlag Berlin Heidelberg

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Liu, Z., Lai, Y. (2009). A Data Mining Framework for Building Intrusion Detection Models Based on IPv6. In: Park, J.H., Chen, HH., Atiquzzaman, M., Lee, C., Kim, Th., Yeo, SS. (eds) Advances in Information Security and Assurance. ISA 2009. Lecture Notes in Computer Science, vol 5576. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02617-1_62

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  • DOI: https://doi.org/10.1007/978-3-642-02617-1_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02616-4

  • Online ISBN: 978-3-642-02617-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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