Tian, Biming, Merrick, Kathryn, Yu, Shui and Hu, Jiankun 2013, A hierarchical PCA-based anomaly detection model, in ICNC 2013 : International Conference on Computing, Networking and Communications, IEEE Computer Society, Piscataway, N.J., pp. 621-625.
A hierarchical intrusion detection model is proposed to detect both anomaly and misuse attacks. In order to further speed up the training and testing, PCA-based feature extraction algorithm is used to reduce the dimensionality of the data. A PCA-based algorithm is used to filter normal data out in the upper level. The experiment results show that PCA can reduce noise in the original data set and the PCA-based algorithm can reach the desirable performance.
Field of Research
080109 Pattern Recognition and Data Mining
Socio Economic Objective
970108 Expanding Knowledge in the Information and Computing Sciences
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