[1]刘启恒,李雪莲,孙孟娜.跨平台工具链探索网络安全知识图谱研究进展与趋势[J].南京师大学报(自然科学版),2025,48(04):128-138.[doi:10.3969/j.issn.1001-4616.2025.04.013]
　Liu Qiheng,Li Xuelian,Sun Mengna.Exploring Research Advancements and Trends in Cybersecurity Knowledge Graphs via Cross-Platform Toolchains[J].Journal of Nanjing Normal University(Natural Science Edition),2025,48(04):128-138.[doi:10.3969/j.issn.1001-4616.2025.04.013]
点击复制

跨平台工具链探索网络安全知识图谱研究进展与趋势()

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
48
期数:
2025年04期
页码:
128-138
栏目:
计算机科学与技术
出版日期:
2025-08-20

文章信息/Info

Title:
Exploring Research Advancements and Trends in Cybersecurity Knowledge Graphs via Cross-Platform Toolchains
文章编号:
1001-4616(2025)04-0128-11
作者:
刘启恒1; 李雪莲1; 2; 孙孟娜1
(1.南京邮电大学外国语学院,江苏 南京 210023)
(2.南京邮电大学信息产业发展战略研究院,江苏 南京 210023)
Author(s):
Liu Qiheng1; Li Xuelian1; 2; Sun Mengna1
(1.School of Foreign Languages,Nanjing University of Posts and Telecommunications,Nanjing 210023,China)
(2.Institute of Information Industry Development Strategy,Nanjing University of Posts and Telecommunication,Nanjing 210023,China)
关键词:
知识图谱; CiteSpace与SciExplorer-LDGAS; 文献计量分析; 网络安全; 网络空间命运共同体; 人工智能技术
Keywords:
knowledge graph; CiteSpace and SciExplorer-LDGAS; bibliometric analysis; cybersecurity; Community of Shared Future in Cyberspace; artificial intelligence technology
分类号:
TP393.08; TP391.1
DOI:
10.3969/j.issn.1001-4616.2025.04.013
文献标志码:
A
摘要:
在数字化时代,网络安全已成为全球性挑战. 网络攻击手段的日益复杂和多变对网络安全领域的研究提出了更高的要求. 本研究基于文献计量方法,融合CiteSpace与SciExplorer-LDGAS工具链,对2011—2024年间的343篇中英文文献(含CNKI中文核心文献84篇、Web of Science核心英文文献259篇)进行系统性分析,探究网络安全知识图谱领域的研究趋势、合作网络及热点演变. 研究结果表明:(1)该领域发文量自2017年起显著增长,2023—2024年达到峰值,反映计算机技术的发展与学术关注度的增强;(2)作者与机构合作呈现区域性聚集特征,中美两国研究贡献领先(分别占比27%和25%),欧美国家合作较多,但其余跨国合作网络稀疏;(3)关键词分析揭示国内外研究侧重差异:国内聚焦技术突破,国外则侧重应用优化; 中英文文献也呈现出显著趋同性,具体聚焦于网络威胁情报、本体构建以及人工智能(AI)等核心方向;(4)研究热点从早期“态势感知”“可视分析”向“知识图谱构建”“攻击模式预测”演进,凸显人工智能技术驱动的防御体系升级需求. 基于此,本文提出需加强跨国、跨机构协作,建立统一的知识共享平台,推动知识图谱技术与多源威胁情报的深度整合,为构建网络空间命运共同体提供理论与工具支撑.
Abstract:
In the digital era,cybersecurity has become a global challenge. With the increasing complexity and variability of cyberattack methods,research in the cybersecurity field faces heightened demands. This study employs bibliometric methods,integrate the CiteSpace and SciExplorer-LDGAS toolchains,to conduct a systematic analysis of 343 Chinese and English literature articles from 2011 to 2024(including 84 Chinese core articles from CNKI and 259 English core articles from Web of Science). The goal is to explore research trends,collaborative networks,and the evolution of hotspots in the domain of cybersecurity knowledge graphs. The findings reveal that:(1)The volume of publications in this field has grown significantly since 2017,peaking in 2023-2024,reflecting advancements in computer technology and increased academic attention;(2)Author and institutional collaborations exhibit regional clustering,with China and the United States leading in research contributions(27% and 25%,respectively),while European and American countries show stronger intra-regional collaboration,though transnational networks remain sparse;(3)Keyword analysis highlights divergent research focuses:domestic studies prioritize technological breakthroughs,whereas international studies emphasize application optimization. Both Chinese and English literature demonstrate significant convergence on core directions such as cyber threat intelligence,ontology construction,and artificial intelligence(AI);(4)Research hotspots have evolved from early themes like "situation awareness" and "visual analytics" to "knowledge graph construction" and "attack pattern prediction",underscoring the demand for AI-driven upgrades in defense systems. Based on these findings,this study proposes enhancing transnational and cross-institutional collaboration,establishing unified knowledge-sharing platforms,and promoting deeper integration of knowledge graph technologies with multi-source threat intelligence,thereby providing theoretical and technical support for building a Community of Shared Future in Cyberspace.

参考文献/References:

[1]习近平:没有网络安全就没有国家安全[EB/OL].(2021-10-10)[2025-1-9]. http://www.qstheory.cn/zhuanqu/2021-10/10/c_1127943608.htm.
[2]SOMMER R,PAXSON V. Outside the closed world:on using machine learning for network intrusion detection[C]//2010 IEEE Symposium on Security and Privacy. Oakland,CA,USA:IEEE,2010:305-316.
[3]LI H,SHI Z,PAN C,et al. Cybersecurity knowledge graphs construction and quality assessment[J]. Complex Intelligent systems,2024(10):1201-1217.
[4]丁兆云,刘凯,刘斌,等. 网络安全知识图谱研究综述[J]. 华中科技大学学报(自然科学版),2021,49(7):79-91.
[5]邢家绵,边晶,康静雨,等. 国内外网络安全评估研究的热点及趋势——基于CiteSpace的知识图谱可视化分析[J]. 电脑知识与技术,2022,18(20):37-40.
[6]肖婉,张舒予. 国外网络欺凌研究热点与实践对策——基于CiteSpace知识图谱软件的量化分析[J]. 比较教育研究,2016,38(4):66-72.
[7]李杰,蔡彬清,许璐. 基于CiteSpace的我国网络空间安全研究态势分析[J]. 福建工程学院学报,2018,16(2):174-178.
[8]马超,陈亚丽. 基于CiteSpace和Vosviewer的国内外网络治理研究的可视化分析[J]. 西南民族大学学报(人文社会科学版),2021,42(8):229-240.
[9]林玲,陈福集. 基于CiteSpace的国内网络舆情研究知识图谱分析[J]. 情报科学,2017,35(2):119-125.
[10]张宁,盛武. 基于CiteSpace的大数据时代信息安全研究现状[J]. 华北水利水电大学学报(社会科学版),2018,34(3):156-160.
[11]陈琴,蒋合领. 基于WoS核心合集的国际智库研究可视化分析[J]. 情报资料工作,2016(1):68-73.
[12]董淑龙,马姜明,辛文杰. 景观视觉评价研究进展与趋势——基于CiteSpace的知识图谱分析[J]. 广西师范大学学报(自然科学版),2023,41(5):1-13.
[13]何静,冯元柳,邵靖雯. 基于CiteSpace的多源数据融合研究进展[J]. 广西师范大学学报(自然科学版),2024,42(5):13-27.
[14]MAHONEY W,GANDHI R A. An integrated framework for control system simulation and regulatory compliance monitoring[J]. International Journal of Critical Infrastructure Protection,2011(4(1)):41-53.
[15]贾焰,亓玉璐,尚怀军,等. 一种构建网络安全知识图谱的实用方法[J]. Engineering,2018,4(1):117-133.
[16]王通,艾中良,张先国. 基于深度学习的威胁情报知识图谱构建技术[J]. 计算机与现代化,2018,(12):21-26.
[17]于丰瑞. 网络威胁技战术情报自动化识别提取研究综述[J]. 计算机工程与应用,2024,60(13):1-22.
[18]董继平,郭启全,高春东,等. 基于图深度学习的漏洞检测[J]. 科技导报,2023,41(13):41-59.
[19]MITRA S,PIPLAI A,MITTAL S,et al. Combating fake cyber threat intelligence using provenance in cybersecurity knowledge graphs[C]//2021 IEEE International Conference on Big Data(Big Data). Piscataway,NJ,USA:IEEE,2021:3316-3323.
[20]安宁,安璐. 跨平台网络舆情知识图谱构建及对比分析[J]. 情报科学,2022,40(3):159-165.
[21]王琪凯,刘孙俊,何俊江,等. 基于表格填充的网络威胁情报关系三元组抽取[J]. 微电子学与计算机,2025,42(7):82-92.
[22]谢腾,杨俊安,刘辉. 基于BERT-BiLSTM-CRF模型的中文实体识别[J]. 计算机系统应用,2020,29(7):48-55.
[23]赖清楠,金建栋,周昌令. 基于大语言模型的网络威胁情报知识图谱构建技术研究[J]. 通信学报,2024,45(S2):33-43.
[24]黄智勇,刘昕宇,林仁明,等. 基于知识图谱的网络攻击预测方法研究及应用[J]. 现代电子技术,2024,47(9):91-96.
[25]周锦,薛钰,杨秉杰,等. 基于深度学习BiLSTM-CRF模型的网络安全知识图谱实体识别方法[J]. 网络安全技术与应用,2024,(9):41-44.
[26]罗养霞,李浩,武晨明. 恶意软件知识图谱的构建与研究[J]. 计算机工程与科学,2025,47(1):86-94.
[27]张玉臣,孙澄,姜迎畅,等. 融合威胁情报与知识图谱的网络攻击溯源方法[J]. 情报杂志,2024,43(8):72-83,91.
[28]SILLS M,RANADE P,MITTAL S. Cybersecurity threat intelligence augmentation and embedding improvement:a healthcare usecase[C]//2020 IEEE International Conference on Intelligence and Security Informatics(ISI). Arlington,VA,USA:IEEE,2020:1-6.
[29]NOUR B,POURZANDI M,QURESHI R K,et al. AUTOMA:automated generation of attack hypotheses and their variants for threat hunting using knowledge discovery[C]//IEEE Transactions on Network and Service Management. Piscataway,NJ,USA:IEEE,2024,21(5):5178-5196.
[30]司成,张红旗,汪永伟,等. 基于本体的网络安全态势要素知识库模型研究[J]. 计算机科学,2015,42(5):173-177.

相似文献/References:

[1]章屹祯,汪 涛,曹卫东,等.全球视野下区域协调发展的经济地理学研究——进展与展望[J].南京师大学报(自然科学版),2020,43(03):78.[doi:10.3969/j.issn.1001-4616.2020.03.013]
　Zhang Yizhen,Wang Tao,Cao Weidong,et al.Economic Geography Research on Regional CoordinatedDevelopment from Global Perspective—Progress and Prospect[J].Journal of Nanjing Normal University(Natural Science Edition),2020,43(04):78.[doi:10.3969/j.issn.1001-4616.2020.03.013]
[2]梁益银,金恒旭,葛潇钦,等.基于文献计量的城市洪涝研究现状及趋势[J].南京师大学报(自然科学版),2025,48(03):21.[doi:10.3969/j.issn.1001-4616.2025.03.003]
　Liang Yiyin,Jin Hengxu,Ge Xiaoqin,et al.Current Status and Trends of Urban Flood Research Based on Bibliometrics[J].Journal of Nanjing Normal University(Natural Science Edition),2025,48(04):21.[doi:10.3969/j.issn.1001-4616.2025.03.003]

备注/Memo

备注/Memo:
收稿日期:2025-04-26.
基金项目:国家社会科学基金项目(WYZL2023JS0013)、江苏省社科应用研究精品工程地方志专项课题重点项目(23SFZA-08)、江苏省“双创博士”项目(JSSCBS20220624).
通讯作者:李雪莲,博士,讲师,研究方向:计算语言学、语料库语言学. E-mail:lixuelian@njupt.edu.cn
更新日期/Last Update: 2025-08-20