您当前的位置:
首页 >
文章列表页 >
Network traffic anomaly detection method based on multi-scale convolution and channel attention mechanism
Papers | 更新时间:2026-02-10
    • Network traffic anomaly detection method based on multi-scale convolution and channel attention mechanism

    • Journal on Communications   Vol. 47, Issue 1, Pages: 184-200(2026)
    • DOI:10.11959/j.issn.1000-436x.2026010    

      CLC: TP393
    • Received:23 October 2025

      Revised:2026-01-11

      Accepted:12 January 2026

      Published:25 January 2026

    移动端阅览

  • Fu Yu,Wang Yujue,Yu Yihan,et al.Network traffic anomaly detection method based on multi-scale convolution and channel attention mechanism[J].Journal on Communications,2026,47(01):184-200. DOI: 10.11959/j.issn.1000-436x.2026010.

  •  
  •  

0

Views

356

下载量

0

CSCD

Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Illicit data resale detection method via an enhanced relational graph convolutional network
Trajectory reconstruction attacks on differential privacy based on a CNN-BiLSTM-Attention hybrid model
THz UM-MIMO system channel estimation algorithm based on deep residual block fixed-point network
MDA-MIM: a radar echo map prediction model integrating multi-scale feature fusion and dual attention mechanism

Related Author

Wang Yuxiang
Zhang Lingcui
Hou Yuqiao
Yang Qian
Niu Ben
XIE Lixia
ZHAO Erkang
YANG Hongyu

Related Institution

State Key Laboratory of Cyberspace Security Defense
School of Cyber Security, University of Chinese Academy of Sciences
Institute of Information Engineering, Chinese Academy of Sciences
School of Computer Science and Engineering, Tianjin University of Technology
College of Cyber Science, Nankai University
0