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Recognition Method of Key Nodes in Command and Control Network Based on Convolutional Neural Network
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Xin CHANG1, Yanbin LI1, Donghui LIU2, 3
Radio Communications Technology | 2025, 51(5) : 1087 - 1101
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Radio Communications Technology | 2025, 51(5): 1087-1101
• Engineering Practice and Application Technology •
Recognition Method of Key Nodes in Command and Control Network Based on Convolutional Neural Network
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Xin CHANG1, Yanbin LI1, Donghui LIU2, 3
Affiliations
  • 1.The 54th Research Institute of CETC, Shijiazhuang 050081, China
  • 2.School of Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
  • 3.Research Institute of Engineering Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
Published: 2025-09-18 doi: 10.3969/j.issn.1003-3114.2025.05.022
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To address the issue of current command and control network key node recognition methods relying on expert knowledge, a method based on convolutional neural networks from the perspective of communication reconnaissance is proposed. Powerful feature extraction capabilities of convolutional neural networks are leveraged to develop an intelligent paradigm for key node recognition. First, the communication relationship information between nodes is transformed into a multi-dimensional information matrix using feature engineering. Then, inspired by the Finite Impulse Response (FIR) filter structure, a Finite Impulse Response Squeeze and Excitation (FIRSE) neural network is proposed. Finally, a dynamic peak detection method is introduced to improve the training strategies and obtain optimal neural network parameters. Experimental results show that compared with typical machine learning and deep learning-based recognition methods, the proposed method offers higher identification accuracy.

command and control network  /  key nodes  /  recognition  /  feature engineering  /  convolutional neural network
Xin CHANG, Yanbin LI, Donghui LIU. Recognition Method of Key Nodes in Command and Control Network Based on Convolutional Neural Network[J]. Radio Communications Technology, 2025 , 51 (5) : 1087 -1101 . DOI: 10.3969/j.issn.1003-3114.2025.05.022
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Year 2025 volume 51 Issue 5
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Article Info
doi: 10.3969/j.issn.1003-3114.2025.05.022
  • Receive Date：2024-05-28
  • Online Date：2026-04-17
  • Published：2025-09-18
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  • Received：2024-05-28
Affiliations
    1.The 54th Research Institute of CETC, Shijiazhuang 050081, China
    2.School of Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
    3.Research Institute of Engineering Management, Shijiazhuang Tiedao University, Shijiazhuang 050043, China
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