摘要
提出了一种基于改进的ART-2神经网络的入侵检测系统,采用新的非线性变换函数和竞争层学习算法克服了ART-2神经网络的“预处理信号畸变”和“同相位不可分”问题,使之更适用于入侵检测,提高了检测的准确率和对未知入侵的自适应识别能力。
The paper presents a new intrusion detection system based on modified ART-2 neural network, adopts new non-linear transfer function and competitive learning algorithm to solve the problem that the same phasic data with different amplitude can't be distinguished by the standard ART-2 neural network and make it more suitable for intrusion detection system. It can raise the accuracy of detection and the ability of adaptively detecting unknown intrusion.
出处
《计算机工程》
EI
CAS
CSCD
北大核心
2005年第7期158-159,192,共3页
Computer Engineering
关键词
入侵检测系统
自适应共振
神经网络
Intrusion detection system(IDS)
Adaptive resonance
Neural network
