计算机应用与软件2023，Vol.40Issue(12)：318-324,349,8.DOI:10.3969/j.issn.1000-386x.2023.12.047
一种面向类别不平衡SSL VPN加密流量识别方法
AN ENCRYPTED TRAFFIC IDENTIFYING METHOD FOR CATEGORY UNBALANCED SSL VPN
摘要
Abstract
Traditional methods are difficult to extract features and have low detection rate when dealing with unbalanced mass high-dimensional data.To solve this problem,the proposed method used the data synthesis oversampling technology(NEDIL)based on the theory of genetic chromosomes to balance the original data set,and then used the bidirectional GRU network traffic identification model based on attention mechanism to identify SSL VPN traffic.This method not only solved the problem of model underfitting or overfitting caused by sample imbalance,and enhanced the differentiation degree of key features,which solved the problem that the general recognition model could not distinguish the difference in importance degree of time series data.The experimental results show that compared with the current typical methods,the proposed method has better recognition accuracy on the public traffic data set,and the overall application recognition accuracy is higher than 92%.关键词
SSL VPN/不平衡数据集/过采样/深度学习/注意力机制Key words
SSL VPN/Unbalanced data set/Oversampling/Deep learning/Attention mechanism分类
信息技术与安全科学引用本文复制引用
王宇航,姜文刚,翟江涛,王晰晨,戴伟东,张帆..一种面向类别不平衡SSL VPN加密流量识别方法[J].计算机应用与软件,2023,40(12):318-324,349,8.基金项目
国家自然科学基金项目(61702235). （61702235）
