Abstract
In this paper, we aim to develop a systematic framework to semi-automate the process of system logs and databases of intrusion detection systems (IDS). We use both Ef-attribute based mining and Es-attribute based mining to mine effective and essential attributes (hence interesting patterns) from the vast and miscellaneous system logs and IDS databases.
This work is supported by grants from 973, 863 and the National Natural Science Foundation of China (Grant No. #90104002 & #2003CB314800 & #2003AA142080 & #60203044) and China Postdoctoral Science Foundation.
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Liu, W., Wu, JP., Duan, HX., Li, X. (2005). New Method for Intrusion Features Mining in IDS. In: Huang, DS., Zhang, XP., Huang, GB. (eds) Advances in Intelligent Computing. ICIC 2005. Lecture Notes in Computer Science, vol 3644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11538059_45
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DOI: https://doi.org/10.1007/11538059_45
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-28226-6
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