空天防御2025，Vol.8Issue(6)：94-102,9.
基于大模型的协议模板和对象模型的智能关联方法
LLM-Based Intelligent Association Between Protocol Templates and Object Models
摘要
Abstract
To bridge the semantic gap resulting from the transmission of external products via heterogeneous communication protocols,in conjunction with the operation of the joint test platform utilizing the built-in standard object model(SDO)subscription-publish mechanism,this paper introduces an intelligent association method and system for protocol template-object models founded on large language models(LLMs).The process took the XML protocol template and interface description model as input,and generated the intermediate representation through structured preprocessing.The local knowledge base was constructed under the retrieval,augmentation,and generation(RAG)framework to uniformly store SDO definitions,historical association pairs,and proprietary corpora.And through the"dual-channel index,"combined with sparse keyword matching and dense semantic vector retrieval,highly recalled candidates for protocol elements and SDO attributes were generated.Subsequently,a lightweight,high-performance large-scale reasoning model was adopted to perform semantic disambiguation and consistency verification on candidate pairs,and the optimal match was output alongside the prompt-word norms and rule constraints.For"strange inputs"such as abbreviations,pinyin,and mixed Chinese-English writing,a multi-agent diversion parsing strategy was introduced,significantly enhancing the robustness against non-standard expressions.The system ultimately automatically generated a standardized XML association relationship list,supporting traceable evidence fragment backlinks and threshold filtering to avoid low-correlation strong matching.The prototype software integrated the full-process modules of file parsing,knowledge retrieval,intelligent matching,and result export.In verifying typical protocol templates and object model scenarios,it demonstrates robust alignment capabilities and engineering availability across languages and naming systems,providing an efficient and scalable semantic mapping path for rapid access to external resources by the joint test platform.关键词
大语言模型/检索增强生成/语义匹配/智能关联/协议模板Key words
large language model/retrieval-augmented generation/semantic matching/intelligent association/protocol template分类
信息技术与安全科学引用本文复制引用
张育圣,许永辉,周宇琦,杜江,魏长安..基于大模型的协议模板和对象模型的智能关联方法[J].空天防御,2025,8(6):94-102,9.基金项目
国家自然科学基金青年C类项目(62403164) （62403164）
