articleJul 1, 2009GREEN OA

A detailed analysis of the KDD CUP 99 data set

University of New Brunswick · National Research Council Canada · +1 more institution

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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.

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Authors

4

Topics & keywords

Keywords
  • Computer science
  • Data mining
  • Anomaly detection
  • Set (abstract data type)
  • Data set
  • Signature (topology)
  • Anomaly (physics)
  • Knowledge extraction
UN Sustainable Development Goals
  • No poverty
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