神经网络技术在网络入侵检测模型及系统中的应用  

Application of neural network technology in network intrusion detection model and system

作　　者：詹沐清[1] 

机构地区：[1]景德镇陶瓷学院,江西景德镇333403

出　　处：《现代电子技术》2015年第21期105-108,共4页Modern Electronics Technique

摘　　要：主要研究包含神经网络模块的网络入侵检测模型及系统,分析传统入侵检测系统的缺陷及神经网络技术在入侵检测中的优势,建立了基于神经网络且包含误用和异常检测的网络入侵检测系统。利用该系统进行了大量入侵检测试验,试验结果表明:所建模型具有较低的漏报率和误报率,可以很好地检测各种网络入侵类型,大大提高网络的安全性能。The network intrusion detection model and system including neural network module are studied mainly. The defects of the traditional intrusion detection system and the advantages of neural network technology applied in intrusion detection are analyzed,and the network intrusion detection system including misuse and abnormal detection based on neural network was established. A large number of intrusion detection tests were carried out by using this system. The test results show that the established model has low missing alarm rate and false alarm rate,can detect a variety of network intrusion types better,and improve the safety performance of the network greatly.

关 键 词：神经网络 入侵检测模型 网络安全 漏报率 误报率 

分 类 号：TN711-34[电子电信—电路与系统]