神经网络在入侵检测中的应用

The Application of Neural Networks In Intrusion Detection

神经网络具有自组织、自学习和推广能力的优势,将其应用于IDS中是目前网络安全领域的研究热点。基于神经网络的入侵检测方法不仅对于已知的攻击模式具有较好的识别能力,而且具有检测未知攻击的能力。介绍了入侵检测的概念和入侵检测系统的分类,分析了入侵检测技术存在的问题,提出了改进BP算法神经网络的入侵检测模型,最后利用MATLAB验证算法改进的有效性。

The artificial neural network has the capability yourself-organization,self-learning and generalization.Application of neural network in Intrusion Detection System will become the focus of network security research at present.This intrusion detection method which based on neural network can not only identify the known attack,but also can detect the new attack and abnormal event.This article introduced the concept of intrusion detection and intrusion detection system of classification,problems in the analysis of intrusion detection techniques.At the same time,the article Proposed improved BP algorithm of neural network model for intrusion detection,finally using MATLAB validation algorithms to improve effectiveness.