无线局域网自动化接入过程安全监测方法  

Security Monitoring Method of Wireless LAN Automatic Access Process

作　　者：高俊 GAO Jun(Henan Provincial Institute of Scientific&Technical Information,Zhengzhou 450018 China)

机构地区：[1]河南省科学技术情报中心,河南郑州450018

出　　处：《自动化技术与应用》2022年第10期137-141,共5页Techniques of Automation and Applications

摘　　要：针对网络用户隐私信息泄露问题,提出基于K-means算法的无线局域网自动化接入过程安全监测方法。对难以识别的离散型数据预处理进行优化,通过函数计算确定新的聚类中心,以类内相似度距离最小和类间相似度距离最大为标准确定k值大小,完成基于K-means算法的WLAN安全监测模型的构建。模型通过K-means聚类算法训练数据建立数据库,利用直推式异常检测算法判断网络中数据是否存在异常,完成无线局域网自动化接入过程安全监测。仿真实验结果表明,所提方法监测准确率与监测效率都明显高于其他方法,提高了无线局域网使用的安全性能,实现安全监测工作的完善。Aiming at the problem of privacy information leakage of network users,a security monitoring method based on K-means algorithm for wireless LAN automatic access process is proposed. After preprocessing the hard to identify discrete data, the new clustering center is determined by function calculation, and the K value is determined according to the minimum similarity distance within the class and the maximum similarity distance between classes, and complete the construction of WLAN security monitoring model based on K-means algorithm. The model uses K-means clustering algorithm to train data to establish a normal behavior database, and uses the direct push anomaly detection algorithm to determine whether there is abnormal data in the network, and completes the security monitoring of wireless LAN automatic access process. Simulation results show that the monitoring accuracy and efficiency of the proposed method are significantly higher than other methods, which greatly improves the security performance of WLAN and realize the improvement of safety monitoring work.

关 键 词：无线局域网 K-MEANS算法 安全监测 直推式异常检测算法 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]