Semi-supervised co-training and active learning based approach for multi-view intrusion detection

@inproceedings{Mao2009SemisupervisedCA,
  title={Semi-supervised co-training and active learning based approach for multi-view intrusion detection},
  author={Ching-Hao Mao and Hahn-Ming Lee and Devi Parikh and Tsuhan Chen and Si-Yu Huang},
  booktitle={SAC},
  year={2009}
}
Although there is immense data available from networks and hosts, a very small proportion of this data is labeled due to the cost of obtaining expert labels. This proves to be a significant bottle-neck for developing supervised intrusion detection systems that rely solely on labeled data. In spite of the data being collected from real network environments and hence potentially holding valuable information for intrusion detection, such systems can not exploit the remaining unlabeled data. In… CONTINUE READING
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Comparative Study of Supervised Machine Learning Techniques for Intrusion Detection

  • F. Gharibian, A GhorbaniA.
  • In Proceeding of the Communication Networks and…
  • 2007
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