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| 基于静态贝叶斯博弈的蠕虫攻防策略绩效评估 |
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刘玉岭1,2,3, 冯登国1, 吴丽辉4, 连一峰1,3
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1.中国科学院 软件研究所 信息安全国家重点实验室,北京 100190;2.信息网络安全公安部重点实验室(公安部第三研究所),上海 201204;3.信息安全共性技术国家工程研究中心,北京 100190;4.中国科学院 办公厅,北京 100864
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| 摘要: |
| 现有蠕虫攻击策略(防护策略)评估方法没有考虑防护策略(攻击策略)变化对攻击策略(防护策略)绩效评估的影响,且防护策略评估忽视了策略实施成本.针对这种情况,构建了基于静态贝叶斯博弈的绩效评估模型 (performance evaluation model based on static Bayesian game,简称PEM-SBG)以及对抗情形下的蠕虫攻防策略绩效评估方法.在模型PEM-SBG 基础上提出的基于灰色多属性理论的防护策略绩效评估方法,综合考虑了成本类和收益类的多个评估属性,有助于提高评估过程的全面性.针对典型的蠕虫攻防场景.利用仿真工具SSFNet 进行了模拟实验,验证了所提出的模型和方法的有效性. |
| 关键词: 绩效评估 静态贝叶斯博弈 灰色多属性 防护策略 |
| DOI：10.3724/SP.J.1001.2012.03997 |
| 分类号: |
| 基金项目:国家高技术研究发展计划(863)(2009AA01Z439); 国家高技术产业化项目信息安全专项; 信息网络安全公安部重点实验室(公安部第三研究所)开放基金(C10606) |
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| Performance Evaluation of Worm Attack and Defense Strategies Based on Static Bayesian Game |
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LIU Yu-Ling1,2, FENG Deng-Guo1, WU Li-Hui3, LIAN Yi-Feng1,4
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1.State Key Laboratory of Information Security, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China;2.Key Laboratory of Information Network Security of Ministry of Public Security (The 3rd Research Institute of Ministry of Public Se;3.Clerical Office, The Chinese Academy of Sciences, Beijing 100864, China;4.National Engineering Research Center for Information Security, Beijing 100190, China
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| Abstract: |
| The existing performance evaluation methods of worm attack strategies (defense strategies) are not considered defense strategies (attack strategies) change’s influence on attack strategies (defense strategies) and performance evaluation of defense strategies are ignoring the implementation cost. In view of this situation, a performance evaluation model based on static Bayesian game (PEM-SBG) is proposed, and the performance evaluation methods of worm attack and defense mechanisms are presented. The performance evaluation method of defense mechanisms is based on gray multiple attributes theory and considers several evaluation metrics about cost and utility, so the evaluation process is much more comprehensive. Finally, the paper uses simulation tools SSFNet to implement simulation experiments under different attack and defense scenarios and validate the method. |
| Key words: performance evaluation, static Bayesion game, grey multiple attributes, defense mechanisms |
