微型电脑应用2018，Vol.34Issue(5)：29-31,39,4.
简化粒子群优化结合SOM的网络入侵检测方法
A Network Intrusion Detection Method Using Simplified Particle Swarm Optimization Algorithm and SOM
摘要
Abstract
For the issue of growing size of the Internet,information of network services is more likely to be exposed to intruders and attackers,and network attacks are becoming more and more complex.A method of network intrusion detection using simplified particle swarm optimization (SPSO) and self organizing mapping (SOM) is proposed.According to the feature discrimination force,the PCA method is used to select the feature,and the non-correlation feature filtering data set noise and low variance feature.The normal mode and anomaly modes are simulated by SOM and Gaussian mixture model (GAMM).The scheme allows the measurement of the activation probability of each network element to detect the exact value of all high frequency attacks and classifies the feature space using the probability SOM mean.In this process,a simplified particle swarm optimization (SPSO) algorithm is used to find a better solution in the neighborhood of the current solution.Based on the KDDCUP99 data set,the experimental results show that the proposed method has a good performance and a higher intrusion detection accuracy (ACC) for common network attacks.关键词
自组织映射/入侵检测系统/简化粒子群优化/KDDCUP99/高斯混合模型Key words
Self organizing mapping/Intrusion detection systems/Simplified particle swarm optimization/KDDCUP99/Gaussian mixture model分类
信息技术与安全科学引用本文复制引用
王红梅..简化粒子群优化结合SOM的网络入侵检测方法[J].微型电脑应用,2018,34(5):29-31,39,4.基金项目
新疆维吾尔自治区高校科研计划青年教师科研启动基金项目(XJEDU2016S085) （XJEDU2016S085）
新疆维吾尔自治区高校教学改革研究项目(2017JG089). （2017JG089）
