A clustering-based method for unsupervised intrusion detections

@article{Jiang2006ACM,
  title={A clustering-based method for unsupervised intrusion detections},
  author={Shengyi Jiang and Xiaoyu Song and Hui Wang and Jian-Jun Han and Qing-Hua Li},
  journal={Pattern Recognition Letters},
  year={2006},
  volume={27},
  pages={802-810}
}
Detection of intrusion attacks is an important issue in network security. This paper considers the outlier factor of clusters for measuring the deviation degree of a cluster. A novel method is proposed to compute the cluster radius threshold. The data classification is performed by an improved nearest neighbor (INN) method. A powerful clustering-based method is presented for the unsupervised intrusion detection (CBUID). The time complexity of CBUID is linear with the size of dataset and the… CONTINUE READING
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