An Approach to Network Intrusion Detection Algorithm Based on BP-HMM
A network intrusion detection framework and its associated algorithm based on BP-HMM are put forward; the training and recognition methods of the algorithm are given. A sheer classifier based on HMM cant give attention to both the strong recognition ability for corresponding objects and maximization of difference lain in different models, so a BP neural network is used to provide state probability output for HMM in the HMM framework. Because of the coarse classification of BP, the limitation of HMM is overcome; the ability of classification and recognition is enhanced. Through the use of the any-path method, the accurate rate of recognition is not only improved, but also an obvious calculation predominance is obtained.
back propagation-hidden Markov model vector quantization forward estimation algorithm backward estimation algorithm any-path method intrusion detection
HUANG Guangqiu REN Dayong
School of Management Xian University of Architecture & Technology Xian, Shaanxi Province 710055, China
国际会议
武汉
英文
1321-1326
2007-07-25（万方平台首次上网日期，不代表论文的发表时间）