【论文阅读】A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems

论文对CICIDS2017数据集进行客观评价，介绍了数据集本身存在的缺陷以及解决方法。
摘要： CICIDS2017是2017年提出的，包含了当下最新的威胁种类和特征，相比于之前的数据集，没有重大的缺陷，但足以使典型的IDS产生偏差。

入侵检测系统需要与时俱进的信息才能够有效的检测到攻击，大量入侵检测系统达到98%准确率，吸引了研究者和企业投入资金和时间为用户提供有效的产品，但是这些模型很少能够被企业所使用在开发真实的IDS中。

CICIDS2017缺陷在于：

数据集过大且过于分散
== 可以进行下采样，但是在采样之前要解决数据类别不平衡的问题才可以==
包含大量的冗余数据
数据高度不平平衡，误导分类器，训练会侧重于样本数量较多的类

在解决数据不平衡问题上，1）将样本数量较多的类进行分割，分成几个类，或者将几个少数类合并成一个类（ == 但是这样会使得样本的多样性减少 == ）

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【论文阅读】A detailed analysis of CICIDS2017 dataset for designing Intrusion Detection Systems

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