Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree

@inproceedings{Chen2005FeatureSA,
  title={Feature Selection and Intrusion Detection Using Hybrid Flexible Neural Tree},
  author={Yuehui Chen and Ajith Abraham and Ju Yang},
  booktitle={ISNN},
  year={2005}
}
Current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything) to the detection process. The purpose of this study is to identify important input features in building an IDS that is computationally efficient and effective. This paper proposes an IDS model based on general and enhanced Flexible Neural Tree (FNT). Based on the pre-defined instruction/operator sets, a flexible… CONTINUE READING
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