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Wenjuan An and Mangui Liang A new intrusion detection method based on SVM with minimum within-class scatter Security and Communication Networks 6

Version of Record online: 18 DEC 2012 | DOI: 10.1002/sec.666

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In this paper, a new classification algorithm, which combines the minimum within-class scatter in Fisher discriminant analysis with traditional support vector machine, is to find an optimal separating hyperplane such that the margin is maximized, whereas the within-class scatter is kept as small as possible. Experimental results show that this new algorithm has better discriminatory power than support vector machine and kernel Fisher discriminant analysis, and it has higher true detection rate and lower false positive rate for intrusion detection systems.

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