改进BP神经网络用于入侵检测

随着网络的不断发展,网络上的信息量在日益增多,人们在网络上的应用也越来越多,网络安全成为十分重要的问题。入侵检测是网络安全的的一个研究热点。本文经过对入侵检测历史与现状的分析和对目前入侵检测技术的研究。针对目前大多数入侵检测系统存在的局限性,提出了一种利用改进BP神经网络算法的入侵检测方法,仿真实验结果表明该算法可以有效地进行入侵检测,使入侵检测的准确性与速度有所提高。

Improved BP Neural Network for Intrusion Detection

As the network continues to develop,the amount of information on the network in the growing number of people on the network more and more applications,network security has become a very important issue.Network security,intrusion detection is a hot research topic.After this history and current situation of intrusion detection analysis and intrusion detection technology of the current study.Most intrusion detection system for the existing limitations,a BP neural network algorithm improved intrusion detection methods,simulation results show that the algorithm can effectively intrusion detection,to intrusion detection accuracy and speed has increased.