A hierarchical PCA-based anomaly detection model

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.

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Title A hierarchical PCA-based anomaly detection model
Author(s) Tian, Biming
Merrick, Kathryn
Yu, Shui
Hu, Jiankun
Conference name Computing, Networking and Communications. Conference (2013 : San Diego, California)
Conference location San Diego, California
Conference dates 28-31 Jan. 2013
Title of proceedings ICNC 2013 : International Conference on Computing, Networking and Communications
Editor(s) [Unknown]
Publication date 2013
Conference series International Conference on Computing, Networking and Communications
Start page 621
End page 625
Total pages 5
Publisher IEEE Computer Society
Place of publication Piscataway, N.J.
Keyword(s) cloud service pricing
M/M/c
utility function
hierarchical
Summary 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.
ISBN 1467352888
9781467352888
Language eng
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category E1 Full written paper - refereed
Copyright notice ©2013, IEEE
Persistent URL http://hdl.handle.net/10536/DRO/DU:30060784

Document type: Conference Paper
Collection: School of Information Technology
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