An Efficient DoS Attacks Detection Method Based on Data Mining Scheme

Abstract:

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To defend against DoS attacks and ensure QoS of web server, we first propose an efficient network anomaly detection method based on TCM-KNN (Transductive Confidence Machines for K-Nearest Neighbors) algorithm. Secondly, we integrate a lot of objective and efficient DoS impact metrics from the perceptions of the end users into TCM-KNN algorithm to build a robust anomaly detection mechanism. Finally, Genetic Algorithm (GA) based instance selection method is introduced to boost the real-time detection performance of our method.

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Periodical:

Edited by:

Yanwen Wu

Pages:

302-307

DOI:

10.4028/www.scientific.net/AMR.267.302

Citation:

X. Chen "An Efficient DoS Attacks Detection Method Based on Data Mining Scheme", Advanced Materials Research, Vol. 267, pp. 302-307, 2011

Online since:

June 2011

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Price:

$35.00

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