Computer Science ›› 2014, Vol. 41 ›› Issue (4): 111-115.

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Intrusion Detection System Based on Improved Naive Bayesian Algorithm

WANG Hui,CHEN Hong-yu and LIU Shu-fen   

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

Abstract: With increasing Internet connectivity and traffic volume,recent intrusion incidents have reemphasized the importance of network intrusion detection system (IDS).According to the deficiency of the Naive Bayesian (NB) algorithm,this paper proposed an improved NB algorithm.This algorithm based on the original model is combined with a parameter of classification control.It can simplify the complexity of the classification of data and optimize the classification accuracy by computed parameter values.The experimental results prove that the algorithm used in the intrusion detection framework can drastically reduce the false alarm rate of IDS,thereby improve the detection efficiency and decrease economic damage brought by the cyber attack.

Key words: Naive Bayesian,IDS,Value attribute,Controlling parameter,False alarm rate

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