基于多阶段攻防信号博弈的最优主动防御

doi:10.3969/j.issn.0372-2112.2017.02.023

电子学报 ›› 2017, Vol. 45 ›› Issue (2): 431-439.DOI: 10.3969/j.issn.0372-2112.2017.02.023

基于多阶段攻防信号博弈的最优主动防御

张恒巍, 李涛

信息工程大学三院, 河南郑州 450001

收稿日期:2015-08-03 修回日期:2016-05-30 出版日期:2017-02-25
- 作者简介:
- 张恒巍,男,1978年出生,河南洛阳人,博士,信息工程大学讲师,研究方向为网络安全行为分析、信息安全风险评估.E-mail:zhw11qd@126.com;李涛,男,1992年出生,甘肃甘谷人,信息工程大学硕士研究生,研究方向为网络安全主动防御.
- 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.13210231002）

Optimal Active Defense Based on Multi-stage Attack-Defense Signaling Game

ZHANG Heng-wei, LI Tao

The Third Institute, Information Engineering University, Zhengzhou, Henan 450001, China

Received:2015-08-03 Revised:2016-05-30 Online:2017-02-25 Published:2017-02-25
- Supported by:
- National Natural Science Foundation of China (No.61303074, No.61309013); Fund of Science and Technology Project of Henan Province (No.13210231002)

摘要/Abstract

摘要：

从网络攻防对抗的实际场景出发，针对具有不完全信息约束的多阶段动态攻防过程，构建了多阶段攻防信号博弈模型.针对多阶段攻防过程中信号作用衰减的问题，提出信号衰减因子进行量化描述.在此基础上，设计了多阶段攻防博弈均衡的求解方法，并给出了最优主动防御策略选取算法.通过仿真实验验证了本文模型和方法的有效性，并且分析总结了多阶段攻防博弈的规律.

关键词: 网络攻防, 多阶段信号博弈, 信号衰减, 博弈均衡, 防御策略

Abstract:

From the real network attack-defense,aimed at the multi-stage and dynamic attack-defense process with the restriction of incomplete information,the multi-stage attack-defense signaling game model is proposed in the paper.Considering attenuation of the signal effect in the multi-stage attack and defense,signal attenuation factor is proposed for the quantification of attenuation.Based on the above,we design the solution for game equilibrium in multi-stage attack and defense.Then the algorithm of optimal active defense strategies selection is proposed.Finally,a simulation experiment is conducted to verify the effectiveness of the model and method proposed in the paper,through which some rules in the multi-stage attack-defense game are concluded.

Key words: network attack and defense, multi-stage signaling game, signaling attenuation, game equilibrium, defense strategies

中图分类号:

TP309

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.

ZHANG Heng-wei, LI Tao . Optimal Active Defense Based on Multi-stage Attack-Defense Signaling Game[J]. Acta Electronica Sinica, 2017, 45(2): 431-439.

参考文献

[1] Zhu Qiang,Li Fang-hua.Game theory of information security[J].Chinese Journal of Electronics,2015,21(3):1472-1486.
[2] Ocevcic H,Nenadic K,Solic K.Game theory:Active defense model and method[J].IEEE Information and Network Security,2015,51(8):395-406.
[3] Gordon L,Loeb M.Budgeting process for information security expenditures[J].Communications of the ACM,2015,49(11):121-125.
[4] WANG Yu-zhuo,YU Jian-ye,QIU Wen.Evolutionary game model and analysis methods for network group behavior[J].Chinese Journal of Computers,2015,38(2):282-300.
[5] JIANG Wei,FANG Bing-xing.Defense strategies selection based on attack-defense game model[J].Journal of Computer Research and Development,2014,47(12):714-723.
[6] White J,Park J S,Kamhoua C A,Kwiat K A.Game theoretic attack analysis in Online Social Network (OSN) services[A].Proceedings of the 2014 International Conference on Social Networks Technology[C].Los Angeles:IEEE,2014.1012-1019.
[7] WANG Jin-dong,YU Ding-kun,ZHANG Heng-wei.Active defense strategy selection based on static bayesian game[J].Journal of Xidian University,2016,43(1):144-151.
[8] LIU Yu-ling,FENG Deng-guo.Worm attack-defense strategy based on static bayesian game[J].Journal of Software,2014,23(12):712-723.
[9] Burke D.Towards a game theory model of information warfare[D].Montgomery,AL:Air force Institute of Technology,Air University,2015.
[10] Wang Chun-lei,Miao Qing,Dai Yi-qi.Network survivability analysis based on stochastic game model[J].Multimedia Information Networking and Security,2014,55(10):199-204.
[11] Yu Min,Liu Chao,Qiu Xin-liang,Zhao Shuang.Modelling and analysis of phishing attack using Stochastic Game[J].Cyberspace Technology,2015,46(3):300-305.
[12] LIN Wang-qun,WANG Hui,LIU Jia-hong.Research on active defense technology in network security based on non-cooperative dynamic game theory[J].Journal of Computer Research and Development,2014,48(11):306-316.
[13] Filler T,Judas J,Fridrich J.Signaling game model:DDOS defense analysis[J].Journal of Security Engineering,2015,39(3):414-417.
[14] ZHANG Hengwei,Han Ji-hong,Yu Ding-kun.Defense policies selection method based on attack-defense signaling game model[J].Journal on Communications,2016,37(5):39-49.
[15] Steven Tadelis.Game Theory:An Introduction[M].Princeton:Princeton University Press,2014.
[16] Richard Lippmann,Joshua W.Haines.Analysis and results of the DARPA off-line intrusion detection evaluation[A].Proceedings of the 17'th International Workshop on Recent Advances in Intrusion Detection[C].New York:ACM,2014.162-182.
[17] Zhu Jian-min,Song Biao,Huag Qi-fa.Evolution game model of of fense-defense for network security based on system dynamics[J].Journal on Communications,2015,35(1):54-61.
[18] ZHANG Hengwei,LI Tao,WANG Jindong.Optimal active defense using dynamic multi-stage signaling game[J].China Communications,2015,12(2):114-122.
[19] Thomas H.Cormen,Charles E.Leisers on,Ronald L.Rivest.Introduction to Algorithms[M].Boston:MIT Press,2009.
[20] 高志伟,姚尧,饶飞.基于漏洞严重程度分类的漏洞预测模型[J].电子学报,2014,42(9):1285-1287. GAO Zhi-wei,YAO Yao,RAO Fei.Predicting model of vulnerabilities based on the type of vulnerability severity[J].Acta Electronica Sinica,2014,42(9):1785-1787.(in Chinese)
[21] 刘奇旭,张翀斌,张玉清.安全漏洞等级划分关键技术研究[J].电子学报,2015,43(1):1779-1785. LIU Qi-xu,ZHANG Chong-bin,ZHANG Yu-qing.Research on key technology of vulnerability threat classification[J].Acta Electronica Sinica,2015,43(1):1779-1785.(in Chinese)
[22] CVSS.Common Vulnerability Scoring System[DB/OL].http://www.cve.mitre.org/,2014-09-17.
[23] Gordon L,Loeb M,Lucyshyn W,Richardson R.2015 CSI/FBI computer crime and security survey[A].Proceedings of the 2014 Computer Security Institute[C].San Francisco:IEEE,2015.48-64.
[24] SI Pengbo,ZHANG Qian,F.Richard.QoS aware dynamic resource management in heterogeneous cloud computing networks[J].China Communications,2014,41(5):144-159.

基于多阶段攻防信号博弈的最优主动防御

Optimal Active Defense Based on Multi-stage Attack-Defense Signaling Game

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