Title :
Network intrusion detection method based on Agent and SVM
Author :
Xiaoqing, Guan ; Hebin, Guo ; Luyi, Chen
Author_Institution :
Beijing Vocational Coll. of Electron. Sci., Beijing, China
Abstract :
It is necessary to study a kind of network intrusion detection method which realizes faster attack detection and response. In order to improve the network intrusion detection precision further, Network intrusion detection method based on Agent and SVM is proposed to recognize the intrusion types in the paper. The network intrusion detection system based Agent and SVM are created. Then, network Intrusion detection model based on SVM is gained, and the process of intrusion detection by SVM is given. The experimental results demonstrate that the presented method in this paper is better than artificial neural network.
Keywords :
computer network security; support vector machines; SVM; artificial neural network; attack detection; network intrusion detection method; support vector machines; Artificial neural networks; Data mining; Educational institutions; IP networks; Intrusion detection; Kernel; Lagrangian functions; Learning systems; Support vector machine classification; Support vector machines; Agent; intrusion detection; network; support vector machine;
Conference_Titel :
Information Management and Engineering (ICIME), 2010 The 2nd IEEE International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-5263-7
Electronic_ISBN :
978-1-4244-5265-1
DOI :
10.1109/ICIME.2010.5477694
