改进遗传算法选择特征在入侵检测中的应用

Application of Improved Ggenetic Algorithm to Select Features in Intrusion Detection,

使用集成学习的方法进行入侵检测过程中,特征选择是关键的一个环节,最佳的特征组合,不但能够降低分类的错误率,而且在分类效率上也有很大的提高。对遗传算法进行改进,并用于入侵检测数据集的特征选择上,经实验证明此方法能够得到较好的集成效果。

Intrusion detection using ensemble learning, in the process, feature selection is an important part. The best feature combination, not only can reduce the classification error rate, but also can improve the classification efficiency. Improved genetic algorithm and using feature selection of intrusion detection data sets, and the experiment proved that this method can get a better integration of results.