Yu-Ting Lu
ChangzhouTextileGarmentInstitute, 213164, Changzhou, China
ABSTRACT
Targeting at various defects of the current intrusion detection technologies, such as the high omission ratio, poor self-learning ability and the relatively high error alarming rate, the paper proposed a intrusion detection algorithm based on improved neural network. According to the experimental results, the intrusion detection result makes full use of the advantages of KPCA and ICA and it boasts ideal intrusion detection performance and the fine learning ability.
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Received: August 07, 2013;
Accepted: November 06, 2013;
Published: November 13, 2013
How to cite this article
Yu-Ting Lu, 2013. The Study on Network Intrusion Detection Technology Based on Improved Principal Component Analysis. Journal of Applied Sciences, 13: 5099-5105.
DOI: 10.3923/jas.2013.5099.5105
URL: https://scialert.net/abstract/?doi=jas.2013.5099.5105
DOI: 10.3923/jas.2013.5099.5105
URL: https://scialert.net/abstract/?doi=jas.2013.5099.5105
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