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基于神经网络的入侵检测系统模型
引用本文:李鸿培,王新梅.基于神经网络的入侵检测系统模型[J].西安电子科技大学学报,1999,26(5):667-671.
作者姓名:李鸿培  王新梅
作者单位:西安电子科技大学综合业务网国家重点实验室!陕西西安710071
摘    要:讨论了利用神经网络设计识别用户异常行为的入侵检测系统的方案,即提取用户正常行为样本的特征来构造用户正常行为的特征轮廓;用神经网络扫描系统的审计迹得到的检测样本与用户特征轮廓进行比较,以两者的偏差作为证据,并结合证据理论来提高检测的正确率.

关 键 词:神经网络  证据理论  计算机网络安全  入侵检测系统模型  入侵检测系统

An intrusion detection system model based on the neural network
LI Hong-pei,WANG Xin-mei.An intrusion detection system model based on the neural network[J].Journal of Xidian University,1999,26(5):667-671.
Authors:LI Hong-pei  WANG Xin-mei
Abstract:An intrusion detection system model based on the neural network and evidence theory is discussed. First we use a neural network to capture the user behavior pattern and to create the user normal behavior profile; then the deviant estimate of the detect samples is given by the neural network and the Dempster Shafer evidence theory is used to fuse the result derived from the neural network at different times, so that the abnormality in the user behavior can be detected more efficiently.
Keywords:neural network  evidence theory  computer networks security  intrusion detection system model  intrusion detection system
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