Abstract：The solution based on multi-approaches of data mining involving k-means, C4.5, Nave Bayes, Bayes net and Co-training is proposed in order to deal with the major problems of intrusion detection dataset such as class balance, class overlapping, noise, distributions etc. The experiment results show its validity.
周荃，赵凤英，王崇骏，陈世福. 数据挖掘方法在入侵检测中的应用研究*[J]. 模式识别与人工智能, 2008, 21(4): 520-526.
ZHOU Quan, ZHAO Feng-Ying, WANG Chong-Jun, CHEN Shi-Fu. Study of Data Mining in Intrusion Detection. , 2008, 21(4): 520-526.
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