关键信息基础设施安全保护技术体系

doi:10.3969/j.issn.1671-1122.2020.11.001

信息网络安全 ›› 2020, Vol. 20 ›› Issue (11): 1-9.doi: 10.3969/j.issn.1671-1122.2020.11.001

关键信息基础设施安全保护技术体系

郭启全¹, 张海霞²()

1.公安部网络安全保卫局,北京 100741
2.中国科学院软件研究所,北京 100190

收稿日期:2020-09-30 出版日期:2020-11-10 发布日期:2020-12-31
通讯作者: 张海霞 E-mail:zhanghx@tca.iscas.ac.cn
作者简介:郭启全（1962—）,男,河北,研究员,硕士,主要研究方向为网络空间安全、网络空间地理学和人工智能|张海霞（1981—）,女,河北,高级工程师,博士,主要研究方向为网络空间安全
基金资助:
国家重点研发计划(2020YFB1806504)

Technology System for Security Protection of Critical Information Infrastructures

GUO Qiquan¹, ZHANG Haixia²()

1. Cyber Security Department, The Ministry of Public Security, Beijing 100741, China
2. Institute of Software, Chinese Academy of Sciences, Beijing 100190, China

Received:2020-09-30 Online:2020-11-10 Published:2020-12-31
Contact: ZHANG Haixia E-mail:zhanghx@tca.iscas.ac.cn

摘要/Abstract

摘要：

关键信息基础设施安全保护是当前网络空间安全的核心任务。文章阐述了开展关键信息基础设施安全保护的指导思想,提出了涵盖采集汇聚层、数据治理层、智慧大脑层、业务应用层的技术体系架构,引入大数据分析、人工智能、知识图谱等新型技术,构建网络空间安全地图,利用智慧大脑实现智能化、精准化的情报挖掘、目标画像、行为推理和预测预警,支撑“实战化、体系化、常态化”安全能力建设,为国家网络安全监管部门和重要行业开展关键信息基础设施安全保护工作提供借鉴。

关键词: 关键信息基础设施, 网络安全, 智慧大脑, 人工智能, 网络空间地图

Abstract:

Security assurance of critical information infrastructure is the core work of cyber security. This paper describes the guiding ideology of security assurance of critical information infrastructure. Afterwards, it proposes the technical architecture including the collection and aggregation layer, data governance layer, intelligent brain layer and business application layer. Technologies such as big data analysis, artificial intelligence and knowledge map are applied to construct cyber security geographic map, realize intelligent datamining, perform accurate portrait of critical targets, conduct behavior reasoning, provide threat early-warning, and finally support the construction of practical, systematic and normalized security abilities. This paper aims to provide the basis for the national cyber security regulatory authorities and important industries to carry out the security assurance work of critical information infrastructures.

Key words: critical information infrastructure, cyber security, intelligent brain, artificial intelligence, cyberspace map

中图分类号:

TP309

郭启全, 张海霞. 关键信息基础设施安全保护技术体系[J]. 信息网络安全, 2020, 20(11): 1-9.

GUO Qiquan, ZHANG Haixia. Technology System for Security Protection of Critical Information Infrastructures[J]. Netinfo Security, 2020, 20(11): 1-9.

图/表 1

参考文献 16

[1]	ZHOU Wen. Ensure the Overall Network Security of Key Information Infrastructure[EB/OL]. http://theory.people.com.cn/n1/2018/0423/c40531-29944021.html People’s Daily Online, 2020-9-19.
	周文. 整体保障关键信息基础设施网络安全[EB/OL]. http://theory.people.com.cn/n1/2018/0423/c40531-29944021.html People’s Daily Online, 2020-9-19.
[2]	FENG Dengguo, ZHAO Xianfeng. The Basics of Information Security[M]. Beijing: Publishing House of Electronics Industry, 2009.
	冯登国, 赵险峰. 信息安全技术概论[M]. 北京: 电子工业出版社, 2009.
[3]	LIN Jingqiang, JING Jiwu, ZHANG Qionglu, et al. Recent Advances in PKI Technologies[J]. Journal of Cryptologic Research, 2015,2(6):487-496.
	林璟锵, 荆继武, 张琼露等. PKI技术的近年研究综述[J]. 密码学报, 2015,2(6):487-496.
[4]	GB/T 22239-2019 Information Security Technology—Base Line for Classified Protection of Cyber Security[S]. Beijing: Standardization Administration of the People's Republic of China, 2019.
	GB/T 22239-2019 信息安全技术网络安全等级保护基本要求[S]. 北京:中国国家标准化管理委员会, 2019.
[5]	CHISMON D, RUKS M. Threat Intelligence: Collecting, Analysing, Evaluating[EB/OL]. https://max.book118.com/html/2018/0814/6114231025001212.shtm, 2020-9-28.
[6]	MCMILLAN R. Definition: Threat Intelligence[R]. Gartner Research. G00249251, 2013.
[7]	BASS T. Intrusion Detection Systems & Multisensor Data Fusion: Creating Cyberspace Situational Awareness[J]. Communications of the ACM, 2000,43(4):99-105.
[8]	WANG Huiqiang, LAI Jibao, ZHU Liang. Survey of Network Situational Awareness System[J]. Computer Science, 2006,33(10):5-10.
	王慧强, 赖积保, 朱亮. 网络态势感知系统研究综述[J]. 计算机科学, 2006,33(10):5-10.
[9]	LUGER G F. Artificial Intelligence[M]. Boston: Pearson Education Inc. , 2008.
[10]	LI Kaifu, WANG Yonggang. Artificial Intelligence[M]. Beijing: Cultural Development Press, 2017.
	李开复, 王咏刚. 人工智能[M]. 北京: 文化发展出版社, 2017.
[11]	LEE Wenke. A Data Mining Framework for Constructing Features and Models for Intrusion Detection Systems[D] Columbia: Columbia University, 1999.
[12]	FORREST S, HOFMEYR S A, SOMAYAJI A., et al. A Sense of Self for Unix Processes[C]//IEEE. Symposium on Security and Privacy, June 6-8, 1996, Los Alamitos, CA. New York:IEEE, 1996: 120-128.
[13]	GRAF R, KING R. Neural Network and Blockchain Based Technique for Cyber Threat Intelligence and Situational Awareness[C]//IEEE. 2018 10th International Conference on Cyber Conflict (CyCon), May 29-June 1, 2008, Tallinn, Republic of Estonia. New York:IEEE, 2018: 409-426.
[14]	NOOR U, ANWAR Z, AMJAD T, et al. A Machine Learning-based FinTech Cyber Threat Attribution Framework Using High-level Indicators of Compromise[J]. Future Generation Computer Systems, 2019,96(2):227-242.
[15]	GUO Qiquan, GAO Chundong, HAO Mengmeng, et al. Develop Visualization Technology of Cyberspace to Support Construction of Comprehensive Prevention and Control System of Cyber Security[J]. Bulletin of Chinese Academy of Sciences, 2020,35(7):917-924.
	郭启全, 高春东, 郝蒙蒙, 等. 发展网络空间可视化技术支撑网络安全综合防控体系建设[J]. 中国科学院院刊 2020, 35(7):917-924.
[16]	GAO Chundong, GUO Qiquan, JIANG Dong, et al. The Theoretical Basis and Technical Path of Cyberspace Geography[J]. Journal of Geographical Sciences, 2019,74(9):1709-1722.
	高春东, 郭启全, 江东, 等. 网络空间地理学的理论基础与技术路径[J]. 地理学报 2019, 74(9):1709-1722.

关键信息基础设施安全保护技术体系

Technology System for Security Protection of Critical Information Infrastructures

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