Abstract
It is an important research topic to improve detection rate and reduce false positive rate of detection model in the field of intrusion detection. This paper adopts an improved boosting method to enhance generalization performance of intrusion detection model based on rule learning algorithm, and presents a boosting intrusion detection rule learning algorithm (BIDRLA). The experiment results on the standard intrusion detection dataset validate the effectiveness of BIDRLA.
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Yang, W., Yun, XC., Yang, YT. (2005). Using Boosting Learning Method for Intrusion Detection. In: Li, X., Wang, S., Dong, Z.Y. (eds) Advanced Data Mining and Applications. ADMA 2005. Lecture Notes in Computer Science(), vol 3584. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11527503_75
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DOI: https://doi.org/10.1007/11527503_75
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-27894-8
Online ISBN: 978-3-540-31877-4
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