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基于博弈论的网络攻防行为建模与态势演化分析

刘小虎 张恒巍 张玉臣 胡浩 程建

刘小虎, 张恒巍, 张玉臣, 胡浩, 程建. 基于博弈论的网络攻防行为建模与态势演化分析[J]. 电子与信息学报, 2021, 43(12): 3629-3638. doi: 10.11999/JEIT200628
引用本文: 刘小虎, 张恒巍, 张玉臣, 胡浩, 程建. 基于博弈论的网络攻防行为建模与态势演化分析[J]. 电子与信息学报, 2021, 43(12): 3629-3638. doi: 10.11999/JEIT200628
Xiaohu LIU, Hengwei ZHANG, Yuchen ZHANG, Hao HU, Jian CHENG. Modeling of Network Attack and Defense Behavior and Analysis of Situation Evolution Based on Game Theory[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3629-3638. doi: 10.11999/JEIT200628
Citation: Xiaohu LIU, Hengwei ZHANG, Yuchen ZHANG, Hao HU, Jian CHENG. Modeling of Network Attack and Defense Behavior and Analysis of Situation Evolution Based on Game Theory[J]. Journal of Electronics & Information Technology, 2021, 43(12): 3629-3638. doi: 10.11999/JEIT200628

基于博弈论的网络攻防行为建模与态势演化分析

doi: 10.11999/JEIT200628
详细信息
    作者简介:

    刘小虎:男,1989年生,博士生,讲师,研究方向为网络攻防博弈、网络建模仿真

    张恒巍:男,1978年生,博士,副教授,研究方向为网络攻防博弈

    张玉臣:男,1977年生,博士,副教授,研究方向为网络空间安全战略

    胡浩:男,1989年生,博士,讲师,研究方向为网络态势感知

    程建:男,1990年生,硕士,讲师,研究方向为网络建模仿真

    通讯作者:

    张恒巍 zhw11qd@163.com

  • 中图分类号: TN915.08; TP393

Modeling of Network Attack and Defense Behavior and Analysis of Situation Evolution Based on Game Theory

  • 摘要: 网络安全本质在对抗。针对现有研究缺乏从博弈视角分析网络攻防行为与态势演化关系的问题,该文提出一种网络攻防博弈架构模型(NADGM),借鉴传染病动力学理论以不同安全状态网络节点密度定义网络攻防态势,分析网络节点安全状态转移路径;以网络勒索病毒攻防博弈为例,使用NetLogo多Agent仿真工具开展不同场景下攻防态势演化趋势对比实验,得出增强网络防御效能的结论。实验结果验证了模型方法的有效性和可行性。
  • 图  1  不完全信息静态贝叶斯博弈树

    图  2  网络节点智能体安全状态转移路径

    图  3  勒索病毒贝叶斯博弈树

    图  4  勒索病毒攻防博弈模型Gambit工程实例

    图  5  初始网络攻防态势

    图  6  RN=100时攻防态势演化

    图  7  RN=200时攻防态势演化

    图  8  RN=300时攻防态势演化

    图  9  RN=363时攻防态势演化

    图  10  RN=400时攻防态势演化

    图  11  RN=500时攻防态势演化

    表  1  勒索病毒攻防类型及策略划分

    攻防类型攻防策略策略含义
    ${\varTheta _{ {\rm{DH} } } }$D1安全意识强,及时升级系统和病毒库等
    D2安全意识强,及时修补漏洞等
    ${\varTheta _{ {\rm{DL} } } }$D3安全意识弱,延迟升级系统和病毒库等
    D4安全意识弱,延迟修补漏洞等
    ${\varTheta _{ {\rm{AH} } } }$A1攻击能力强,熟练运用漏洞扫描攻击等
    A2攻击能力强,熟练运用社会工程学攻击等
    ${\varTheta _{ {\rm{AL} } } }$A3攻击能力弱,勉强运用漏洞扫描攻击等
    A4攻击能力弱,勉强运用社会工程学攻击等
    下载: 导出CSV

    表  2  不同策略组合下攻防收益

    防御策略攻击策略
    A1A2A3A4
    D1(530,800)(550,780)(800,360)(820,330)
    D2(410,910)(420,890)(780,380)(800,350)
    D3(120,1580)(130,1560)(240,770)(260,740)
    D4(100,1820)(110,1940)(210,810)(220,780)
    下载: 导出CSV

    表  3  研究成果对比

    文献博弈信息态势演化分析网络攻防实验场景网络节点规模态势展现效果
    文献[7]完全信息缺乏实物攻防环境节点数≤10
    文献[8]完全信息缺乏实物攻防环境节点数≤10
    文献[9]不完全信息缺乏实物攻防环境节点数≤10
    文献[12]不完全信息不详细NetLogo多Agent仿真节点数≥1000直观
    本文不完全信息传染病动力学NetLogo多Agent仿真节点数≥1000直观
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-07-29
  • 修回日期:  2021-05-28
  • 网络出版日期:  2021-07-13
  • 刊出日期:  2021-12-21

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