Title :
Intrusion detection method research based on optimized self-buildup clustering neural network
Author :
Qiao, Rui ; Chen, Bo
Author_Institution :
Dept. of Inf. Eng., Wuhan Univ. of Technol., China
Abstract :
This paper puts forward a method of bringing neural network to bear intrusion detection. When the average error can´t decrease any longer, the hereditary algorithm will be used to continuatively train the network in the interest of acquiring optimized join parameter. The network structure and network joining parameter will evolve at the same time by the neural network and hereditary algorithm. The convergence effect is good and the adaptivity is strong, suitable for real-time processing.
Keywords :
genetic algorithms; learning (artificial intelligence); neural nets; pattern classification; pattern clustering; security of data; hereditary algorithm; intrusion detection system; neural net training; optimized self-buildup clustering neural network; pattern classification; Clustering algorithms; Computer errors; Delay effects; Expert systems; Face detection; IP networks; Information security; Intrusion detection; Neural networks; Optimization methods;
Conference_Titel :
Information Acquisition, 2004. Proceedings. International Conference on
Print_ISBN :
0-7803-8629-9
DOI :
10.1109/ICIA.2004.1373338
