Correlation-Based Feature Selection for Intrusion Detection Design

@article{Chou2007CorrelationBasedFS,
  title={Correlation-Based Feature Selection for Intrusion Detection Design},
  author={Te-Shun Chou and Kang K. Yen and Jun Luo and Niki Pissinou and Kia Makki},
  journal={MILCOM 2007 - IEEE Military Communications Conference},
  year={2007},
  pages={1-7}
}
In a large amount of monitoring network traffic data, not every feature of the data is relevant to the intrusion detection task. In this paper, we aim to reduce the dimensionality of the original feature space by removing irrelevant and redundant features. A correlation-based feature selection algorithm is proposed for selecting a subset of most informative features. Six data sets retrieved from UCI databases and an intrusion detection benchmark data set, DARPA KDD99, are used to train and to… CONTINUE READING
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