电子学报 ›› 2018, Vol. 46 ›› Issue (9): 2222-2228.DOI: 10.3969/j.issn.0372-2112.2018.09.025

• 学术论文 • 上一篇    下一篇

基于随机演化博弈模型的网络防御策略选取方法

黄健明1, 张恒巍1,2   

  1. 1. 信息工程大学三院, 河南郑州 450001;
    2. 数学工程与先进计算国家重点实验室, 河南郑州 450001
  • 收稿日期:2017-07-06 修回日期:2017-10-16 出版日期:2018-09-25 发布日期:2018-09-25
  • 通讯作者: 张恒巍
  • 作者简介:黄健明 男,1992年出生于湖南张家界,硕士研究生,主要研究方向为网络安全主动防御.E-mail:hjm-i-jbb@126.com
  • 基金资助:
    国家自然科学基金(No.61303074,No.61309013);河南省科技计划基金(No.12210231003,No.13210231002)

A Method for Selecting Defense Strategies Based on Stochastic Evolutionary Game Model

HUANG Jian-ming1, ZHANG Heng-wei1,2   

  1. 1. The Third Institute, Information Engineering University, Zhengzhou, Henan 450001, China;
    2. State Key Laboratory of Mathematical Engineering and Advanced Computing, Zhengzhou, Henan 450001, China
  • Received:2017-07-06 Revised:2017-10-16 Online:2018-09-25 Published:2018-09-25

摘要: 针对攻防博弈系统中存在攻防策略集和系统运行环境改变等各类随机干扰因素的问题,传统确定性博弈模型无法准确描述攻防博弈过程.利用非线性Itó随机微分方程构建随机演化博弈模型,用于分析攻防随机动态演化过程.通过求解,并根据随机微分方程稳定性判别定理对攻防双方的策略选取状态进行稳定性分析,设计出基于随机攻防演化博弈模型的安全防御策略选取算法.最后,通过仿真验证了不同强度的随机干扰对攻防决策演化速率的影响,且干扰强度越大,防御者更倾向于选择强防御策略,攻击者更倾向于选择强攻击策略.本文模型和方法能够用于网络攻击行为预测和安全防御决策.

关键词: 网络安全, 网络攻防, 博弈论, 有限理性, 演化博弈, 网络防御, Itó随机微分方程, 策略选取

Abstract: In the network attack-defense game systems,there are many stochastic factors,such as changes of attack-defense strategy sets and system operating environment.The traditional deterministic game model can not describe the game process of network attack and defense accurately.This paper constructed an attack-defense stochastic evolutionary game model by adapting the nonlinear Itó stochastic differential equations.The model can be applied to analyze the stochastic evolutionary process of network attack and defense.In addition,the stability of the strategy selection of attack and defense was analyzed according to the discriminant theorem of stochastic differential equations.Besides,an algorithm to select the security defense strategies based on stochastic attack-defense evolutionary game model was designed.Finally,the simulations demonstrate that the different intensity influences of stochastic interference on the speed of decision-making evolution of attack and defense.The attackers and defenders are more inclined to choose strong strategies when the game system has great intensity of interference.The model and the method proposed in this paper can provide guidance for attack behavior prediction and defense strategy selection.

Key words: network security, network attack-defense, game theory, bounded rationality, evolutionary game, network defense, Itó, stochastic differential equation, strategy selection

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