Computer Science ›› 2015, Vol. 42 ›› Issue (2): 134-136.doi: 10.11896/j.issn.1002-137X.2015.02.029

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Intrusion Detection Method Based on Multi-label and Semi-supervised Learning

QIAN Yan-yan, LI Yong-zhong and YU Xi-ya   

  • Online:2018-11-14 Published:2018-11-14

Abstract: The concerned problem of machine learning is how the systems automatically improve the classification performance with the increase of experience,which is consistent with IDS.Therefore,it has become an effective program to put the theories and methods of machine learning into IDS.In this paper,a multi-label lazy learning approach named ML-KNN was applied to intrusion detection systems.KDD CUP99 data set was implemented to evaluate the ML-KNN algorithm.The simulation results show that this method can achieve higher detection rate and lower false positive rate compared to other algorithms.

Key words: Multi-label learning,ML-KNN algorithm,Semi-supervised learning,Intrusion detection

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