无线传感网络中一种基于RF-GAN模型的入侵检测算法  

An Intrusion Detection Algorithm Based on RF-GAN Model in Wireless Sensor Networks

作　　者：黄俊萍[1] HUANG Junping(School of Information Management,Minnan University of Science and Technology,Shishi Fujian 362700,China)

机构地区：[1]闽南理工学院信息管理学院,福建石狮362700

出　　处：《长沙大学学报》2024年第2期23-28,共6页Journal of Changsha University

基　　金：福建省中青年教师教育科研项目“基于推荐算法的大学生就业管理系统的设计与研究”,编号:JAT200746。

摘　　要：针对现有无线传感网络入侵检测算法存在的效率低、精度差等问题,提出基于RFGAN模型的无线传感网络入侵检测算法。首先,采集无线传感网络运行数据,通过去噪、缺失补偿等步骤,完成对原始数据的预处理;然后,利用RF-GAN模型提取无线传感网络运行特征;最后,通过提取特征与检测标准的匹配,得出网络入侵检测结果。理论分析及实验结果表明:优化设计方法的入侵类型误检率明显更低,入侵数据量检测误差为0.015GB,相较于现有检测算法具有一定优势。Aiming at the problems of low efficiency and poor accuracy of existing intrusion detection algorithms for wireless sensor networks,an intrusion detection method based on RF-GAN model is proposed.Firstly,the operation data of wireless sensor networks is collected,and the original data is pre-processed by denoising and loss compensation.Then,the RF-GAN model is used to extract the operating characteristics of the wireless sensor networks.Finally,the results of network intrusion detection are obtained by matching the extracted features with the detection criteria.Theoretical analysis and experimental results show that the error detection rate of intrusion type is lower and intrusion data volume detection error is 0.015 GB,which has certain advantages compared with the existing detection algorithms.

关 键 词：RF-GAN模型 无线传感网络 网络入侵检测 特征提取 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]