计算机与现代化 ›› 2023, Vol. 0 ›› Issue (11): 51-56.doi: 10.3969/j.issn.1006-2475.2023.11.008

• 人工智能 • 上一篇    下一篇

基于渗流理论的关键信息基础设施网络资产重要性评估方法

  

  1. (1.成都信息工程大学网络空间安全学院,四川 成都 610225; 2.先进密码技术与系统安全四川省重点实验室,四川 成都 610225;3.网络空间安全态势感知与评估安徽省重点实验室,安徽 合肥 230037)
  • 出版日期:2023-11-29 发布日期:2023-11-29
  • 作者简介:黄雨婷(1996—),女,四川广元人,硕士研究生,研究方向:网络安全,E-mail:1465372808@qq.com; 陈麟(1973—),男,四川成都人,教授,博士,研究方向:网络安全; 通信作者:林宏刚(1976—),男,四川成都人,教授,博士,研究方向:网络安全,E-mail: 8644163@qq.com。
  • 基金资助:
    国家242信息安全计划(2021-037); 网络空间安全态势感知与评估安徽省重点实验室开放课题(CSSAE-2021-002)

An Importance Assessment Method of Network Assets in Critical Information Infrastructure Based on Percolation Theory

  1. (1. School of Cyberspace Security, Chengdu University of Information Engineering, Chengdu 610225, China; 
    2. Sichuan Key Laboratory of Advanced Cryptography and System Security, Chengdu 610225, China; 
    3. Anhui Key Laboratory of Cyberspace Security Situational Awareness and Assessment, Hefei 230037, China)
  • Online:2023-11-29 Published:2023-11-29

摘要: 摘要:对关键信息基础设施网络资产重要度的评估是目前国家重点关注方向。针对当前网络资产重要性评估忽略业务链进而影响结果准确性和有效性的问题,本文基于网络业务供需关系构建“信息-物理-用户”3层耦合网络,提出一种基于网络渗流理论的资产重要性评估方法:在构建的耦合模型上应用改进的网络渗流理论,并结合节点渗流概率及节点的资源输送能力损失描述失效在网络中的传播,然后综合节点失效前后网络最大业务交付负载变化率与用户影响等级双重指标来区分节点的不同影响力。最后以电力行业为背景进行仿真实验,结果表明,本文方法具有较高的准确性,为网络资产的重要性评估提供了理论依据。

关键词: 关键词:关键信息基础设施, 网络渗流理论, 关键资产, 耦合网络, 失效传播

Abstract: Abstract: The assessment of the importance of network assets of critical information infrastructures is a key national concern at present. To address the problem that the current network asset importance assessment ignores the business chain and thus affects the accuracy and validity of the results, this paper constructs a three-layer coupled network of “information-physical-users” based on the supply-demand relationship of network services, and proposes an asset importance assessment method based on the network percolation theory: we apply the improved network percolation theory to the coupled model and describe the propagation of failure in the network by combining the percolation probability of nodes and the loss of resource delivery capacity of nodes, and then integrate the change rate of maximum service delivery load and user impact level of nodes before and after failure to distinguish the different impacts of nodes. Finally, simulation experiments are conducted in the context of the electric power industry, and the results show that the method in this paper has high accuracy and provides a theoretical basis for the importance assessment of network assets.

Key words: Key words: critical information infrastructure, network percolation theory, critical assets, coupled networks, failure propagation

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