Title :
A hybrid method of rough set and support vector machine in network intrusion detection
Author :
Zhiguo, Liu ; Jincui, Kang ; Yuan, Li
Author_Institution :
ShiJiaZhuang Coll., Shijiazhuang, China
Abstract :
In order to avoid the network intrusion, the network intrusion detection method is studied and developed. In the paper, a hybrid method of rough set and support vector machine are adopted to network intrusion detection. The detection model includes the data reduction by rough set and network intrusion recognition by support vector machine. The 680 cases are collected to study the superiority of the proposed in the paper, where 460 cases are applied as the training data and 220 cases are applied as the testing data. Normal support vector machine is adopted to compare with the hybrid method of rough set-support vector machine. The experimental results show that the detection accuracy of rough set-support vector machine detection method than that of support vector machine.
Keywords :
rough set theory; security of data; support vector machines; data reduction; network intrusion detection; rough set method; support vector machine; Accuracy; Data models; Intrusion detection; Probes; Support vector machines; Testing; Training data; detection method; hybrid method; network intrusion; support vector machine;
Conference_Titel :
Signal Processing Systems (ICSPS), 2010 2nd International Conference on
Conference_Location :
Dalian
Print_ISBN :
978-1-4244-6892-8
Electronic_ISBN :
978-1-4244-6893-5
DOI :
10.1109/ICSPS.2010.5555562