摘要
指挥信息系统的服务共享和开放导致其面临更多的服务资源毁伤和信息欺骗攻击风险,有效的攻击风险评估亟待解决。针对指挥信息系统应用层攻防中信息不完备性和不确定性带来的攻击效能评估困难问题,建立指标因素数量为2+5+17的指挥信息系统应用层攻击3级评估指标体系,提出双因子主观、客观赋权法确定评估指标权重,应用反向传播人工神经网络理论建立具有学习机制和持续改进能力的模糊隶属函数,设计了单一攻击效能和多种攻击效能的模糊综合评估方法。实验结果表明:该方法不仅能够实现单一攻击效果的模糊量化和多种攻击的模糊排序,而且指标集更完整、赋权方法更综合、模糊隶属函数更具适用性。
The service sharing and opening of command information system lead to more service resource damages and information spoofing risk in its application layer attack.For difficult effectiveness evaluation problem due to the incomplete information and uncertainty in offensive and defensive attack of application layer of command information system,a three-level evaluation index system with index factor number of 2+5+17 is established for application layer attack of command information system.A two-factor subjective and objective weighting method is presented to determine the evaluation index weights.The theory of BP artificial neural network is used to establish the fuzzy membership function with learning mechanism and continuously improved capability.A fuzzy comprehensive evaluation method is designed for the single attack efficiency and a variety of attack effectiveness.The experimental results show that the proposed method can be used not only to achieve the fuzzy quantization of single attack effect and fuzzy ranking of multiple attacks,but also have more complete index set,more comprehensive weighting method and more applicable fuzzy membership function.
作者
黄迎春
牟鑫明
HUANG Yingchun;MOU Xinming(School of Information Science and Engineering, Shenyang Ligong University, Shenyang 110159, Liaoning, China;School of Computer Science and Engineering, Northeastern University, Shenyang 110169, Liaoning, China)
出处
《兵工学报》
EI
CAS
CSCD
北大核心
2020年第5期932-940,共9页
Acta Armamentarii
基金
辽宁省自然科学基金项目(20180550216)
沈阳理工大学专业学位硕士研究生课程建设项目(2017PM02)
辽宁省特聘教授基金项目(2017年)。
关键词
指挥信息系统
应用层攻击
人工神经网络
模糊综合评估
攻击效能
command information system
application layer attack
artificial neural network
fuzzy comprehensive evaluation
attack effectiveness
