DocumentCode
2094934
Title
Study on improvement of recognition ability of intrusion detection system
Author
Yanwei, Fu ; Yingying, Zhu
Author_Institution
Network Center, Changzhou Univ., Changzhou, China
fYear
2010
fDate
11-14 Nov. 2010
Firstpage
5
Lastpage
8
Abstract
This paper integrates PCA method and optimized LMBP neural network into intrusion detection system. The feasibility and efficiency of the optimized algorithm are approved by utilizing the KDDCUP99 dataset, constructing suitable training samples and testing samples and using MATLAB simulation experiment. Experiment shows that the improved algorithm has obvious superiority in training times and accuracy.
Keywords
backpropagation; neural nets; principal component analysis; security of data; KDDCUP99 dataset; MATLAB simulation; PCA method; intrusion detection system; optimized LMBP neural network; principal component analysis; recognition ability improvement; Computational modeling; Databases; Jacobian matrices; Optimization; Intrusion Detection; Levenberg-Marquardt(LM) Algorithm; Neural Network; Principal Component Analysis;
fLanguage
English
Publisher
ieee
Conference_Titel
Communication Technology (ICCT), 2010 12th IEEE International Conference on
Conference_Location
Nanjing
Print_ISBN
978-1-4244-6868-3
Type
conf
DOI
10.1109/ICCT.2010.5689069
Filename
5689069
Link To Document