As network-based technologies become omnipresent, intrusion detection and prevention for these systems become increasingly important. This paper proposed a modified mutual information-based feature selection algorithm (MMIFS) for intrusion detection on the KDD Cup 99 dataset. The C4.5 classification method was used with this feature selection method. In comparison with dynamic mutual information feature selection algorithm (DMIFS), we can see that most performance aspects are improved. Furthermore, this paper shows the relationship between performance, efficiency and the number of features selected.
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机译：随着基于网络的技术的普及，针对这些系统的入侵检测和预防变得越来越重要。提出了一种改进的基于互信息的特征选择算法（MMIFS），用于KDD Cup 99数据集的入侵检测。 C4.5分类方法与此特征选择方法一起使用。与动态互信息特征选择算法（DMIFS）相比，我们可以看到大多数性能方面都得到了改善。此外，本文显示了性能，效率和所选功能数量之间的关系。
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