计算机应用与软件2024，Vol.41Issue(12)：334-340,366,8.DOI:10.3969/j.issn.1000-386x.2024.12.046
基于双向GRU和CNN的恶意网络流量检测方法
MALICIOUS NETWORK TRAFFIC DETECTION METHOD BASED ON BIDIRECTIONAL GRU AND CNN
摘要
Abstract
To solve the problems of insufficient accuracy and poor generalization of current malicious network traffic detection technology,a malicious network traffic detection method based on bidirectional GRU and CNN is proposed.Bidirectional GRU and CNN were used to extract temporal and spatial features of network traffic data in parallel,and self-attention mechanism was added to calculate the importance of features.Experiments were carried out on CIC-IDS2017 dataset.The results show that the accuracy of the detection method in multi-class classification and binary classification are 99.77%and 99.82%respectively,which is superior to other detection methods.关键词
恶意网络流量检测/门控循环单元/卷积神经网络/数据特征/自注意力机制Key words
Malicious network traffic detection/GRU/CNN/Data characteristics/Self-attention mechanism分类
信息技术与安全科学引用本文复制引用
戚子健,柳毅..基于双向GRU和CNN的恶意网络流量检测方法[J].计算机应用与软件,2024,41(12):334-340,366,8.基金项目
国家自然科学基金项目(61572144). （61572144）
