A hybrid system for reducing the false alarm rate of anomaly intrusion detection system

@article{Om2012AHS,
  title={A hybrid system for reducing the false alarm rate of anomaly intrusion detection system},
  author={Hari Om and Aritra Kundu},
  journal={2012 1st International Conference on Recent Advances in Information Technology (RAIT)},
  year={2012},
  pages={131-136}
}
In this paper, we propose a hybrid intrusion detection system that combines k-Means, and two classifiers: K-nearest neighbor and Naïve Bayes for anomaly detection. It consists of selecting features using an entropy based feature selection algorithm which selects the important attributes and removes the irredundant attributes. This algorithm operates on the KDD-99 Data set; this data set is used worldwide for evaluating the performance of different intrusion detection systems. The next step is… CONTINUE READING
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