Network traffic cognition model based on space-time fractals

TANG Pingping; ZHANG Hui; DONG Yuning; DONG Guoqing

doi:10.11959/j.issn.1000-436x.2025091

您当前的位置：

首页 >

文章列表页 >

Network traffic cognition model based on space-time fractals

Correspondences | 更新时间：2025-06-03

- Network traffic cognition model based on space-time fractals
- Journal on Communications Vol. 46, Issue 5, Pages: 258-271(2025)
- 作者机构：
  
  1.安徽师范大学物理与电子信息学院，安徽芜湖 241002
  2.南京邮电大学通信与信息工程学院，江苏南京 210003
  3.安徽华东光电技术研究所有限公司，安徽芜湖 241002
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China(2020YFB2104004);The Key Research and Development Program of Jiangsu Province(BE2021725);The Natural Science Foundation of Anhui Province(2308085Y02;2208085MF155);The Natural Science Foundation of the Higher Education Institutions of Anhui Province(KJ2021A0124);The Anhui Postdoctoral Scientific Research Program Foundation(2024C946)
- DOI：10.11959/j.issn.1000-436x.2025091
  CLC： TN919
- Received：10 March 2025，
  
  Revised：2025-05-09，
  
  Published：25 May 2025
- 稿件说明：
移动端阅览
汤萍萍,张晖,董育宁等.基于空时分形的网络流量认知模型[J].通信学报,2025,46(05):258-271.

TANG Pingping,ZHANG Hui,DONG Yuning,et al.Network traffic cognition model based on space-time fractals[J].Journal on Communications,2025,46(05):258-271.
汤萍萍,张晖,董育宁等.基于空时分形的网络流量认知模型[J].通信学报,2025,46(05):258-271. DOI： 10.11959/j.issn.1000-436x.2025091.

TANG Pingping,ZHANG Hui,DONG Yuning,et al.Network traffic cognition model based on space-time fractals[J].Journal on Communications,2025,46(05):258-271. DOI： 10.11959/j.issn.1000-436x.2025091.

Views

1002

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Research on traffic representation in network anomaly detection

Network intrusion detection method based on VAE-CWGAN and fusion of statistical importance of feature

Adaptive random early detection algorithm based on network traffic level grade prediction

Network traffic anomaly detection method based on multi-scale characteristic

Network queue scheduling algorithm based on self-similar traffic level grading prediction

Related Author

CHANG Heyu

ZHANG Bin

SUN Jianwen

Yu FU

Taotao LIU

Kun WANG

Xueyuan DUAN

Chengsheng PAN

Related Institution

Cryptography Engineering Institute, Information Engineering University

School of Mathematics and Information Engineering, Xinyang Vocational and Technical College

College of Computer and Information Technology, Xinyang Normal University

Department of Information Security, Naval University of Engineering

School of Automation, Nanjing University of Science and Technology

AI导读

AI脑图

AI问答

⁰

Network traffic cognition model based on space-time fractals

DOI：10.11959/j.issn.1000-436x.2025091