基于特征选择算法的网络实时入侵检测系统研究  

Network Real-time Intrusion Detection System Based on Feature Selection Algorithms

作　　者：邓兴华[1] DENG Xinghua(Shangqiu College,Shangqiu 476000,China)

机构地区：[1]商丘学院

出　　处：《现代信息科技》2019年第20期157-159,共3页Modern Information Technology

摘　　要：为了保障网络系统的安全与稳定,需要进行网络入侵检测模型研究,目前具有代表性的检测系统是基于遗传算法找出网络入侵的特征子集,但该系统检测准确性较低且训练时间过长。为此,本文将特征选择算法应用到网络实时入侵检测系统中,提出了一种基于特征选择的实时入侵检测方法。通过搭建非法入侵检测实验平台将该方法与基于遗传算法的网络入侵检测方法做比较,实验结果表明,该方法在检测攻击的准确率方面优于另一入侵检测系统,并且所需检测时间也短于另一检测系统。In order to ensure the security and stability of network system,it is necessary to study the network intrusion detection model. At present,the representative detection system is based on genetic algorithm to find the characteristic subset of network intrusion,but the detection accuracy of the system is low and the training time is too long. Therefore,feature selection algorithm is applied to network real-time intrusion detection system,and a real-time intrusion detection method based on feature selection is proposed. This method is compared with the network intrusion detection method based on genetic algorithm by building an experimental platform of illegal intrusion detection. The experimental results show that this method is superior to the other intrusion detection system in detection accuracy,and the detection time is shorter than the other detection system.

关 键 词：特征选择算法 网络入侵 实时检测系统 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术] TP181[自动化与计算机技术—计算机科学与技术]