摘要
为增强指挥信息系统韧性,提升资源使用效费比,必须把有限资源投入到对系统韧性影响最为显著的重要节点上。分析指挥信息系统韧性过程,以攻击发生后指挥信息系统在规定恢复时间内的平均功能水平来评估其韧性;建立指挥信息系统模型和节点模型,根据各个节点韧性增加/减少相同比率时,对系统韧性的影响程度来度量节点重要性,提出基于蒙特卡罗仿真的节点重要性计算方法;通过仿真实验对指挥信息系统韧性过程,节点重要性度量方法及其性能、应用场景等进行验证。实验结果表明,该度量方法能有效区分指挥信息系统节点的重要性,且在单调性和精确性方面具有一定优势,可应用于指挥信息系统规划设计、运维管理、应急抢修等阶段的韧性增强。
In order to enhance the resilience of the command information system and improve the efficiency cost ratio of resource utilization,limited resources must be invested in the important nodes that have the most significant impact on the system resilience.This paper analyzes the resilience process of the command information system and evaluates its resilience based on the average functional level of the command information system within the specified recovery time after the attack.The command information system model and node model are established.The node importance is measured according to the degree of impact on system resilience when the resilience of each node increases/decreases at the same rate.A node importance calculation method based on Monte Carlo simulation is proposed.Through simulation experiments,the resilience process of the command information system,the node importance measurement method and its performance,application scenarios are verified.The experimental results show that the measurement method can effectively distinguish the importance of the command information system nodes,and has certain advantages in monotony and accuracy.It can be used to enhance the resilience of the command information system in the planning and design,operation and maintenance management,emergency repair and other stages.
作者
岳地久
李建华
王哲
YUE Dijiu;LI Jianhua;WANG Zhe(School of Information and Navigation,Air Force Engineering University,Xi’an 710077,China;Unit 94755 of the PLA,Zhangzhou 363000,China;School of Information and Communication,National University of Defense Technology,Wuhan 430010,China)
出处
《系统工程与电子技术》
EI
CSCD
北大核心
2024年第4期1320-1329,共10页
Systems Engineering and Electronics
关键词
指挥信息系统
韧性
节点重要性
功能水平
蒙特卡罗仿真
command information system
resilience
node importance
functional level
Monte Carlo simulation
