Title :
Risk Evaluation of Network Security Based on NLPCA-RBF Neural Network
Author :
Ran Jingxue ; Xiao Bo
Author_Institution :
Modern Educ. Tech. Dept., Minzu Univ. of China, Beijing, China
Abstract :
About the risk evaluation of network security, a new assessment method based on Nonlinear Principal Component Analysis (NLPCA) is given. The principle and process of NLPCA-RBF is introduced in detail. At last, its superiority is indicated by example. It not only can reduce the dimension of input vector, but also can reserve the nonlinear characteristic of the network by nonlinearity. It is a new evaluation method of more quickly, more effective, more exact.
Keywords :
computer network security; principal component analysis; radial basis function networks; risk analysis; NLPCA-RBF neural network; network security risk evaluation; new assessment method; nonlinear principal component analysis; risk evaluation; Analytical models; Artificial neural networks; Indexes; Principal component analysis; Risk analysis; Security; Training; Network security; Nonlinear Principal Component Analysis (NLPCA); Radial Basic Function Neural Network (RBFNN); Risk evaluation;
Conference_Titel :
Multimedia Information Networking and Security (MINES), 2010 International Conference on
Conference_Location :
Nanjing, Jiangsu
Print_ISBN :
978-1-4244-8626-7
Electronic_ISBN :
978-0-7695-4258-4
DOI :
10.1109/MINES.2010.89
