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A hierarchical PCA-based anomaly detection model

conference contribution
posted on 2013-01-01, 00:00 authored by B Tian, K Merrick, Shui Yu, J Hu
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.

History

Event

Computing, Networking and Communications. Conference (2013 : San Diego, California)

Pagination

621 - 625

Publisher

IEEE Computer Society

Location

San Diego, California

Place of publication

Piscataway, N.J.

Start date

2013-01-28

End date

2013-01-31

ISBN-13

9781467352888

ISBN-10

1467352888

Language

eng

Publication classification

E1 Full written paper - refereed

Copyright notice

2013, IEEE

Title of proceedings

ICNC 2013 : International Conference on Computing, Networking and Communications

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