广义RBF神经网络预测模型在入侵预测中的应用  

The Application of Generalized RBF Neural Network Predicted Module in Intrusion Prediction

作　　者：仓怀明[1] 米根锁[1] 王景波[1] 

机构地区：[1]兰州交通大学,甘肃兰州730070

出　　处：《计算机安全》2010年第12期52-54,共3页Network & Computer Security

摘　　要：利用径向基函数RBF神经网络具有的分类、预测、自学习的功能,建立RBF网络预测模型并将其应用于入侵预测中来实现检测已知攻击、预测未知攻击,对检测到的网络攻击实时响应。Based on the function of classifying ability、prediction and rapidity of study of RBF neural network,a predicted module of RBF neural network is created in intrusion prediction to detect the cyber attack which has been known and predict the unknown cyber attack,including the real time response in detecting the attack on the internet.

关 键 词：入侵预测技术 广义的RBF神经网络 网络攻击 

分 类 号：TP311.1[自动化与计算机技术—计算机软件与理论]