Abstract
With the increased usage of computer networks, network intrusions have greatly threatened the Internet infrastructures. Traditional signature-based intrusion detection often suffers from an ineffectivity to those previously “unseen” attacks. In this paper, we analyze the network intrusions from a new viewpoint based on data field and propose branch and bound tree to lessen computation complexity. Finally, we evaluated our approach over KDD Cup 1999 data set.
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© 2006 Springer-Verlag Berlin Heidelberg
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Xie, F., Bai, S. (2006). Detecting Novel Network Attacks with a Data Field. In: Chen, H., Wang, FY., Yang, C.C., Zeng, D., Chau, M., Chang, K. (eds) Intelligence and Security Informatics. WISI 2006. Lecture Notes in Computer Science, vol 3917. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11734628_8
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DOI: https://doi.org/10.1007/11734628_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-33361-6
Online ISBN: 978-3-540-33362-3
eBook Packages: Computer ScienceComputer Science (R0)