基于多阶段Markov信号博弈的移动目标防御最优决策方法

doi:10.12263/DZXB.20191070

电子学报 ›› 2021, Vol. 49 ›› Issue (3): 527-535.DOI: 10.12263/DZXB.20191070

基于多阶段Markov信号博弈的移动目标防御最优决策方法

蒋侣¹, 张恒巍^1,2, 王晋东¹

1. 战略支援部队信息工程大学三院, 河南郑州 450001;
2. 河南省信息安全重点实验室, 河南郑州 450001

收稿日期:2019-09-19 修回日期:2020-10-26 出版日期:2021-03-25
- 通讯作者:
- 张恒巍
- 作者简介:
- 蒋侣男,1995年出生,四川广安人,战略支援部队信息工程大学硕士,助理工程师,主要研究方向为移动目标防御、网络安全与攻防对抗;王晋东 男,1966年出生,山西洪桐人,战略支援部队信息工程大学教授,主要研究方向为网络与信息安全、云资源管理.
- 基金资助:
- 河南省科技攻关计划基金 (No.182102210144）

A Markov Signaling Game-theoretic Approach to Moving Target Defense Strategy Selection

JIANG Lü¹, ZHANG Heng-wei^1,2, WANG Jin-dong¹

1. The Third Institute, PLA SSF Information Engineering University, Zhengzhou, Henan, 450001, China;
2. Henan Key Laboratory of Information Security, Zhengzhou, Henan 450001, China

Received:2019-09-19 Revised:2020-10-26 Online:2021-03-25 Published:2021-03-25
- Corresponding author:
- ZHANG Heng-wei
- Supported by:
- Technology Research and Development Program Fund of Henan Province (No.182102210144)

摘要/Abstract

摘要： 随着移动目标防御技术研究的不断深入，移动目标防御策略选取问题成为当前研究的热点问题之一，本文提出一种基于多阶段Markov信号博弈模型的移动目标防御最优策略选取方法.首先，结合攻防实际，提出实施攻击所需构建的攻击链模型.其次，在考虑状态随机跳变的基础上，将多阶段信号博弈模型与Markov决策过程相结合，构建基于多阶段Markov信号博弈的移动目标防御模型.同时，引入Logistic映射刻画攻防博弈系统中可能造成概率更新过程失真的随机干扰因素.在形式化建模的基础上，设计折扣收益目标函数，并提出均衡求解算法，给出最优防御策略选取算法.最后，通过仿真实验验证模型和方法的有效性.

关键词: 移动目标防御, Markov决策, 多阶段信号博弈, 最优策略选取, logistic映射

Abstract: With the development of the research on Moving Target Defense (MTD) technique, how to effectively select the optimal strategy of moving target defense has become an urgent issue in the current research. To solve this problem, we propose a MTD optimal strategy selection method based on multi-stage Markov signaling game model. Firstly, combined with the actual attack-defense process, we construct an attack chain model that attackers need to build to carry out the attack. Secondly, due to the random jump between states, we combine multi-stage signaling with Markov Decision Process (MDP) to construct the corresponding MTD model. Meanwhile, we adopt Logistic mapping to characterize the stochastic interference factors that may cause the distortion of the probability updating in the attack-defense process. Additionally, on the basis of formally modeling, we design an objective function with discounted total payoff. Besides, we give a solution method for multi-stage signaling game equilibrium and design an optimal defense strategy selection algorithm for MTD. Finally, the simulation demonstrates the effectiveness and feasibility of the proposed model and method.

Key words: moving target defense, Markov decision, multi-stage signaling game, optimal strategy selection, logistic mapping

中图分类号:

TP309

蒋侣, 张恒巍, 王晋东. 基于多阶段Markov信号博弈的移动目标防御最优决策方法[J]. 电子学报, 2021, 49(3): 527-535.

JIANG Lü, ZHANG Heng-wei, WANG Jin-dong . A Markov Signaling Game-theoretic Approach to Moving Target Defense Strategy Selection[J]. Acta Electronica Sinica, 2021, 49(3): 527-535.

参考文献

[1] Bin-Xing F.A hierarchy model on the research fields of cyberspace security technology[J].Chinese Journal of Network & Information Security,2015,1(01):2-7.
[2] Jajodia S.Moving Target Defense:Creating Asymmetric Uncertainty for Cyber Threats[M].New York:Springer-Verlag,2011.42-45.
[3] 蔡桂林,王宝生,王天佐,罗跃斌,王小峰,崔新武.移动目标防御技术研究进展[J].计算机研究与发展,2016,53(05):968-987. CAI G L,WANG B S,WANG T Y,et al.Research on development ofmoving target defense technology[J].Journal of Computer Research and Development,2016,53(05):968-987.(in Chinese)
[4] 刘效武,王慧强,吕宏武,禹继国,张淑雯.网络安全态势认知融合感控模型[J].软件学报,2016,27(08):2099-2114. LIU X W,WANG H Q,LV H W,et al.Fusion-based cognitive awareness-control model for network security situation[J].Journal of Software,2016,27(08):2099-2114.(in Chinese)
[5] 朱建明,王秦.基于博弈论的网络空间安全若干问题分析[J].网络与信息安全学报,2015,1(01):43-49. ZHU J M,WANG Q.Analysis of cyberspace security based on game theory[J].Chinese Journal of Network and Information Security,2015,1(01):43-49.(in Chinese)
[6] Pratyusa K.Manadhata.Game theoretic approaches to attack surface shifting[J].ACM Transactions on Information and System Security,2017,23(2):145-153.
[7] Carter K M,Riordan J F,Okhravi H.A game theoretic approach to strategy determination for dynamic platform defenses[A].Proceedings of the First ACM Workshop on Moving Target Defense[C].New York:ACM,2014.21-30
[8] Kambhampati S,et al.Moving target defense for web applications using bayesian stackelberg games:(extended abstract)[A].2016 International Conference on Autonomous Agents and Multiagent Systems[C].Singapore:AAMAS,2016.1377-1378.
[9] Filler T,Judas J,Fridrich J.Signaling game model:DDOS defense analysis[J].Journal of Security Engineering,2016,39(3):414-417.
[10] Zhang H,Dingkun Y U,Han J,et al.Network security threat assessment based on the signaling game[J].Journal of Xidian University,2016,43(3):137-143..
[11] 张恒巍,余定坤,韩继红,王晋东,李涛.基于攻防信号博弈模型的防御策略选取方法[J].通信学报,2016,37(05):51-61. ZHANG H W,YU D K,HAN J H,et al.Network security threat assessment based on the signaling game[J].Journal on Communications,2016,37(05):51-61.(in Chinese)
[12] Okhravi H,Comella A,Robinson E,et al.Creating a cyber moving target for critical infrastructure applications using platform diversity[J].International Journal of Critical Infrastructure Protection,2014,5(1):30-39.
[13] Feng X,Zheng Z,Cansever D.A signaling game model for moving target defense[A].INFOCOM 2017-IEEE Conference on Computer Communications[C].Piscataway:IEEE,2017.1-9.
[14] Huang S R,Zhang H W,et al.Markov differential game for network defense decision-making method[J].IEEE Access,2018,6:39621-39634
[15] Lei C,Zhang H Q,Wan L M,et al.Incomplete information Markov game theoretic approach to strategy generation for moving target defense[J].Computer Communications,2018,116:184-199.
[16] 刘江,张红旗,刘艺.基于不完全信息动态博弈的动态目标防御最优策略选取研究[J].电子学报,2018,46(1):82-89. LIU J,ZHANG H Q,LIU Y.Research on optimal selection of moving target defense policy based on dynamic game with incomplete information[J].Acta Electronica Sinica,2018,46(1):82-89.(in Chinese)
[17] Zhu Q,Başar T.Game-theoretic approach to feedback-driven multi-stage moving target defense[A].International Conference on Decision and Game Theory for Security[C].Berlin:Springer,2013.246-263.
[18] Manadhata P K,Wing J M.An attack surface metric[J].IEEE Transactions on Software Engineering,2011,37(3):371-386.
[19] Drew Fudenberg,Jean Tirole.Game Theory[M].Boston:Massachusetts Institute of Technology Press,2012.270-295.
[20] Gao X,Zhu Y F.DDos Defense mechanism analysis based on signaling game model[A].Proceedings of the 2013 5th International Conference on Intelligent Human-Machine Systems and Cybernetics[C].Piscataway:IEEE Press,2013.414-417.
[21] Zangeneh V,Shajari M.A cost-sensitive move selection strategy for moving target defense[J].Computers & Security,2018,75(JUN.):72-91.
[22] Sengupta S,Chowdhary A,Huang D,et al.General sum Markov games for strategic detection of advanced persistent threats using moving target defense in cloud networks[A].International Conference on Decision and Game Theory for Security[C].Berlin:Springer,2019.492-512
[23] Maleki H,Valizadeh S,Koch W,et al.Markov modeling of moving target defense games[A].Proceedings of the 2016 ACM Workshop on Moving Target Defense[C].New York:ACM,2016.81-92.
[24] Gordon L,Loeb M,Lucyshyn W,Richardson R.2014 CSI/FBI computer crime and security survey[A].Proceedings of the Computer Security Institute[C].San Francisco,California:IEEE Press,2014.11-34.

基于多阶段Markov信号博弈的移动目标防御最优决策方法

A Markov Signaling Game-theoretic Approach to Moving Target Defense Strategy Selection

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

[1]	张恒巍, 黄世锐. Markov微分博弈模型及其在网络安全中的应用[J]. 电子学报, 2019, 47(3): 606-612.
[2]	张恒巍, 黄健明. 基于Markov演化博弈的网络防御策略选取方法[J]. 电子学报, 2018, 46(6): 1503-1509.
[3]	张恒巍, 李涛, 黄世锐. 基于攻防微分博弈的网络安全防御决策方法[J]. 电子学报, 2018, 46(6): 1428-1435.
[4]	张恒巍, 李涛. 基于多阶段攻防信号博弈的最优主动防御[J]. 电子学报, 2017, 45(2): 431-439.
[5]	李赵红, 侯建军. 基于Logistic混沌映射的DCT域脆弱数字水印算法[J]. 电子学报, 2006, 34(12): 2134-2137.