DocumentCode
1868515
Title
Intrusion detection research based on improved PSO and SVM
Author
Liu Ning ; Zhao Jianhua
Author_Institution
Department of Computer Science, ShangLuo University, 726000, China
fYear
2012
fDate
3-5 March 2012
Firstpage
1263
Lastpage
1266
Abstract
Based on the thought of crossover operation and mutation operation in genetic algorithm, this paper improves particle swarm optimization algorithm. The improved particle swarm optimization algorithm is used to optimize penalty parameter c and kernel function parameters g of SVM and the optimized model named new-PSO-SVM is established. KDD Cup 99 intrusion detection data set is used to carry out experiment. The results show that PSO optimization improves the classification accuracy rate of SVM.
Keywords
Intrusion detection; Particle swarm optimization algorithm; Support vector machine;
fLanguage
English
Publisher
iet
Conference_Titel
Automatic Control and Artificial Intelligence (ACAI 2012), International Conference on
Conference_Location
Xiamen
Electronic_ISBN
978-1-84919-537-9
Type
conf
DOI
10.1049/cp.2012.1209
Filename
6492816
Link To Document