Title :
Incremental intrusion detecting method based on SOM/RBF
Author :
Tian, Li-ye ; Liu, Wei-peng
Author_Institution :
Dept. of Electron. & Inf. Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
Abstract :
An incremental intrusion detecting model is proposed in this paper. This model integrates unsupervised Self Organizing Map and supervised Radial Basis Function to complete incremental learning. Self Organizing Map can get new type intrusion information and generate new nodes in Radial Basis Function. By this model, intrusion of unknown type can be detected online. Experiment results show our model could detect new type intrusions without forgetting the old ones.
Keywords :
learning (artificial intelligence); radial basis function networks; security of data; self-organising feature maps; RBF; SOM; incremental intrusion detection; incremental learning; supervised radial basis function; unsupervised self organizing map; Artificial neural networks; Cybernetics; Intrusion detection; Machine learning; Neurons; Tin; Training; Artificial neural network; Intrusion detection system; RBF; SOM; incremental learning;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580770
