A detailed analysis of the KDD CUP 99 data set

Mahbod Tavallaee, E. Bagheri, Wei Lu, A. Ghorbani
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引用次数: 3487

Abstract

During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks, and KDDCUP'99 is the mostly widely used data set for the evaluation of these systems. Having conducted a statistical analysis on this data set, we found two important issues which highly affects the performance of evaluated systems, and results in a very poor evaluation of anomaly detection approaches. To solve these issues, we have proposed a new data set, NSL-KDD, which consists of selected records of the complete KDD data set and does not suffer from any of mentioned shortcomings.
对KDD CUP 99数据集的详细分析
在过去的十年中,异常检测已经引起了许多研究人员的关注,以克服基于签名的入侵防御系统在检测新型攻击方面的弱点,而KDDCUP'99是最广泛使用的用于评估这些系统的数据集。在对该数据集进行统计分析后,我们发现了两个重要的问题,这些问题严重影响了评估系统的性能,并导致对异常检测方法的评估非常差。为了解决这些问题,我们提出了一个新的数据集,NSL-KDD,它由完整的KDD数据集的选定记录组成,并且没有上述任何缺点。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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