Abstract
In this paper, we apply data mining techniques to construct intrusion detection patterns. We mine both system audit data and network traffic data for consistent and useful patterns of program and user behavior, and use an iterative low-frequency-finder mining algorithm to find the low frequency but important patterns.
This work is supported by grants from 973, 863 and the National Natural Science Foundation of China (Grant No. #90104002 & #2003CB314800 & #2003AA142080 & #60203044) and NISAC 2004-R-3-917-A-01.
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Liu, W., Wu, JP., Duan, HX., Li, X. (2005). New Algorithm Mining Intrusion Patterns. In: Wang, L., Jin, Y. (eds) Fuzzy Systems and Knowledge Discovery. FSKD 2005. Lecture Notes in Computer Science(), vol 3614. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11540007_96
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DOI: https://doi.org/10.1007/11540007_96
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28331-7
Online ISBN: 978-3-540-31828-6
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