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A node device-type identification method based on large language models and retrieval-augmented generation
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Guozheng YANG1, 2, Chiyu CHEN1, Zhaobin SHEN1, 2, Dongzhen QI1, Junyu PAN1
Information Countermeasure Technology | 2025, 4(5) : 42 - 53
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Information Countermeasure Technology | 2025, 4(5): 42-53
• Research Articles •
A node device-type identification method based on large language models and retrieval-augmented generation
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Guozheng YANG1, 2, Chiyu CHEN1, Zhaobin SHEN1, 2, Dongzhen QI1, Junyu PAN1
Affiliations
  • 1College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
  • 2Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation, Hefei 230037, China
doi: 10.12399/j.issn.2097-163x.2025.05.003
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In large-scale cyberspace mapping，rapidly and accurately detecting node information and identifying the operational status of devices is one of the core research contents. Currently，the version iteration speed of cyberspace devices is accelerating，and a large number of new-type devices are constantly emerging. How to track and identify the device type of the measured node has become a new challenge that needs to be solved urgently. Aiming at the problem that current research relies too much on existing knowledge and cannot adapt to device upgrade changes，a node device type identification method based on large language model（LLM）and retrieval-augmented generation（RAG）technology was proposed. First，relevant data were collected from RFC documents and Internet device manufacturer websites，and a knowledge vector database was constructed based on the embedding model.Then，the detected node feature information was encoded，and relevant background knowledge was retrieved from the vector database. The retrieved knowledge and node feature information were jointly constructed into prompts for the LLM. The reasoning ability of the LLM was used to identify the device type of the probed node. Finally，the effectiveness and performance of the method were verified through ablation experiments and real-network tests.

cyberspace mapping  /  LLM  /  RAG  /  device type identification
Guozheng YANG, Chiyu CHEN, Zhaobin SHEN, Dongzhen QI, Junyu PAN. A node device-type identification method based on large language models and retrieval-augmented generation[J]. Information Countermeasure Technology, 2025 , 4 (5) : 42 -53 . DOI: 10.12399/j.issn.2097-163x.2025.05.003
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doi: 10.12399/j.issn.2097-163x.2025.05.003
  • Receive Date：2025-07-07
  • Online Date：2026-04-23
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  • Received：2025-07-07
  • Revised：2025-07-24
Affiliations
    1College of Electronic Engineering, National University of Defense Technology, Hefei 230037, China
    2Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation, Hefei 230037, China
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