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基于多决策树算法的网络入侵检测
Intrusion detection based on algorithm of multi-decision tree
【摘要】 将一个大数据集分割成若干个子数据集,在每个子数据集上使用决策树算法进行挖掘,用投票的方式将多棵决策树的结果结合起来,形成全局的判断。将这种方法应用于网络入侵检测,试验表明,该方法不仅提高了数据挖掘算法对海量数据的处理能力,而且降低了误判率。
【Abstract】 A big data set was firstly divided into several small sub-datasets, and algorithm of decision tree was used on each sub-datasets. A global decision was finally gotten combining multi decision trees by voting. This method was applied to network intrusion detection. The result of experiment shows that the method can not only improve capability of processing a big data set, but also reduce the ratio of misdiagnose.
【基金】 湖南省自然科学基金项目(OOJJY2059)
- 【文献出处】 计算机工程与设计 ,Computer Engineering and Design , 编辑部邮箱 ,2004年04期
- 【分类号】TP393.08
- 【被引频次】12
- 【下载频次】191