基于权重k邻近的通信网络安全漏洞自动化检测  

Automated detection of security vulnerabilities in communication networks based on weighted k-neighborhoods

作　　者：吕连 谢东刚 LV Lian XIE Donggang(Guangxi Vocational&Technical Institute of Industry,Nanning 530001,China)

机构地区：[1]广西工业职业技术学院,南宁530001

出　　处：《自动化与仪器仪表》2024年第4期21-24,31,共5页Automation & Instrumentation

基　　金：2023年度广西高校中青年教师科研基础能力提升项目《基于大数据的高职院校网络安全态势感知系统构建与应用》(2023KY1312)。

摘　　要：无线通信网络的安全漏洞检测是保护无线通信网络安全的重要任务,传统检测方法存在效率低下和错误率高的问题。因此,研究将权重概念引入到K邻近分类算法中,将其用于构建一种新型的无线通信网络的安全漏洞自动化检测方法。首先利用k邻近对网络安全漏洞进行检测,然后再引入权重概念,以提升漏洞检测的性能,最后利用数据集来验证构建方法的性能。结果表明在相同的漏洞检测背景下,权重k邻近对漏洞的检测准确性平均值为93.26%,在200条漏洞数据中,检测耗时4.2 s。这表明构建的检测方法对于无线通信网络的安全保护具有一定的实际意义,具有较高的准确性和鲁棒性,有助于提高无线通信网络的安全性和可靠性。Security vulnerability detection in wireless communication networks is an important task to protect the security of wireless communication networks.Traditional detection methods suffer from inefficiency and high error rate.Therefore,the study proposes an automated detection method for security vulnerabilities in wireless communication networks based on weighted k-neighborhood.Firstly,network security vulnerabilities are detected using k-neighborhood,and then the concept of weights is introduced to improve the performance of vulnerability detection,and finally,a dataset is used to verify the performance of the constructed method.The results show that under the same vulnerability detection context,the average accuracy of vulnerability detection by weighted k-neighborhood is 93.26%,and the detection takes 4.2 s in 200 vulnerability data.This indicates that the constructed detection method is of practical significance for the security protection of wireless communication networks with high accuracy and robustness,which can help to improve the security and reliability of wireless communication networks.

关 键 词：权重 K近邻算法 通信网络 安全漏洞 自动化 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]