数据挖掘技术在网络安全中的应用

Application of Data Mining for Network Security

研究网络安全问题,网络入侵方式具有多样性。未授权滥用网络资源,给网络安全带来影响,对网络入侵检测系统实时性要求比较高。而当前网络入侵检测系统存在检测速度慢,检测正确率低,不能适应网络入检测发展。为了保证网络安全,根据入侵检测系统要求和人工免疫原理提出一种基于人工免疫原理的网络入侵检测系统,用于弥补目前在网络入侵检测方面的一些缺陷。最后对网络入侵检测系统进行构建和仿真。仿真结果表明,人工免疫原理的网络入侵检测系统加快了网络入侵检测速度,提高了入侵检测的正确率,有效的降低入侵漏报率,为网络入侵检测提供了一种新的检测工具。

Research network security.Network intrusions are of diversity,and the current network intrusion detection systems have the limitations of slow detection speed and low detection accuracy.In order to guarantee the network security,according to the requirements of intrusion detection system and artificial immune theory,a network intrusion detection system was proposed based on artificial and immune principle to overcome the defects in the current network intrusion detections.Finally,network intrusion detection system was built and simulated.The simulation results show that the network intrusion detection system based on artificial immune can increase the network intrusion detection rate,improve the intrusion detection accuracy,and reduce the invasion fail rate effectively.It provides a new testing tool for network intrusion detection.