Research of Intrusion Detection Based on Ensemble Learning Model

Abstract:

In order to improve the detection accuracy of the intrusion detection, the proposed ensemble learning model is applied to the intrusion detection. This method can significantly improve the generalization capability and flexibly. Compared to the single classification method, despite choosing the ensemble classifiers for data detection can cause an increase of the additional overhead, ultimately the detection accuracy can be improved obviously. The experimental results with the KDD dataset further verify the significant efficiency of ensemble learning model.

• Periodical: Applied Mechanics and Materials (Volumes 336-338)
• Pages: 2376-2380
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.336-338.2376
• Online since: July 2013
• Authors: Yang Li, Jian Lin Li, Song Jie Yue, Zhi Wang
• Keywords: Classifier, Ensemble Learning, Intrusion Detection

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