网络安全评估技术综述
Survey on Technology of Network Security Assessment
DOI: 10.12677/CSA.2015.51003, PDF,  被引量    科研立项经费支持
作者: 赵 孟, 谭玉波：河南工业大学信息科学与工程学院，河南 郑州
关键词: 互联网；信息技术；网络安全；网络安全评估；Internet； Information Technology； Network Security； Network Security Assessment
摘要: 互联网和信息技术的快速发展，使网络深深的融入到人们的生活中。然而，丰富的互联网服务应用也带来了更多的网络安全问题，网络安全评估技术是当前处理网络安全问题的一种策略。在阐述网络安全评估技术的基本概念、研究意义的基础上，给出了网络安全评估的体系结构，主要从基于数学模型的方法、基于知识推理的方法和基于模式识别的方法三方面分析其研究现状，讨论现有的技术的优势和不足，并探讨了未来的发展方向。
Abstract: With the rapid development of Internet and information technology, the network has been deeply integrated into our lives. However, the rich services and applications of the Internet bring more security problems. Technology of network security assessment is a strategy to deal with the prob-lems of network security at present. The basic concepts and research significance are shed light on. This paper described the architecture of network security assessment, and analyzed the research status mainly focusing on the method based on mathematical model, the method based on know-ledge reasoning and the method based on pattern recognition. Then the advantages and disad-vantages were pointed out respectively. Finally, some future research directions were given at the end.
文章引用：赵孟, 谭玉波. 网络安全评估技术综述[J]. 计算机科学与应用, 2015, 5(1): 18-24. https://dx.doi.org/10.12677/CSA.2015.51003

参考文献

[1] 吴金宇 (2013) 网络安全风险评估关键技术研究. 博士论文, 北京邮电大学, 北京.
[2] 邢栩嘉, 林闯, 蒋屹新 (2004) 计算机系统脆弱性评估研究. 计算机学报, 1, 1-11.
[3] 张剑锋 (2013) 网络安全态势评估若干关键技术研究. 博士论文, 国防科学技术大学, 长沙.
[4] 韦勇, 连一峰, 冯登国 (2009) 基于信息融合的网络安全态势评估模型. 计算机研究与发展, 3, 353-362.
[5] Qi, Y.L. and An, H.L. (2010) The evaluation model of network se-curity based on fuzzy rough sets. In: Qi, Y.L. and An, H.L., Eds., Advances in Wireless Networks and Information Sys-tems, Springer, Berlin, 517-525.
[6] Helmer, G., Wong, J., Slagell, M., et al. (2002) A software fault tree approach to requirements analysis of all intrusion detection system. Requirements Engineering Journal, 4, 207-220.
[7] 张涛, 胡铭曾, 云晓春, 等 (2005) 计算机网络安全性分析建模研究. 通信学报, 12, 100-109.
[8] Schneier, B. (1999) Attack Trees. Dr. Dobb’s Journal, 24, 21-29.
[9] Clark, K., Tyree, S., Dawkins, J., et al. (2004) Qualitative and quantitative analytical techniques for network security assessment. Proceedings of 2004 Information Assurance Workshop of the 5th Annual IEEE SMC, Hawaii, IEEE Press, 321-328.
[10] 王辉, 刘淑芬 (2007) 改进的最小攻击树攻击概率生成算法. 吉林大学学报(工学版), 5, 153-156.
[11] 段友祥, 王海峰 (2007) 基于改进攻击树的网络攻击模式形式化研究. 中国石油大学报(自然科学版), 1, 144- 147.
[12] Dacier, M., Deswartes, Y. and Kaaniche, M. (1996) Quantitative assessment of operational security models and tools. Technical Report Research Report 96439, LAAS.
[13] Phillips, C. and Swiler, L. (1998) A graph-based system for network-vulnerability analysis. Proceedings of the Workshop on New Security Paradigms, Charlottesville, 22-26 September 1998, 71-79.
[14] 方明, 徐开勇, 杨天池, 孟繁蔚, 禹聪 (2013) 基于攻击图的分布式网络风险评估方法. 计算机科学, 2, 139-144.
[15] 陈小军, 方滨兴, 谭庆丰, 张浩亮 (2014) 基于概率攻击图的内部攻击意图推断算法研究. 计算机学报, 1, 62-72.
[16] 陈靖, 王冬海, 彭武 (2013) 基于动态攻击图的网络安全实时评估. 计算机科学, 2, 133-138.
[17] Xie, P., Li, J.H., Ou, X.M., Liu, P. and Levy, R. (2010) Using Bayesian networks for cyber security analysis. Proceedings of the 40th IEEE/IFIP International Conference on Dependable Systems and Network, Chicago, 28 June-1 July 2010, 211-220.
[18] Poolsappasit, N., Dewai, R. and Ray, I. (2012) Dynamic security risk management using Bayesian attack graphs. IEEE Transactions on Dependable and Secure Computing, 9, 61-74.
[19] Frigault, M. and Wang, L. (2008) Measuring network security using Bayesian network-based attack graphs. Proceedings of the 32nd Annual IEEE International Conference on Computer Software and Applications, Turku, 28 July-1 August 2008, 698-703.
[20] Sabata, B. and Ornes, C. (2006) Multi-source evidence fusion for cyber-situation assessment. Proceedings of Multisensor, Multisource Information Fusion Conference, Bellingham, 18 April 2006, 1-9.
[21] Qu, Z.-Y., Li, Y.-Y. and Li, P. (2010) A network security situation evaluation method based on D-S evidence theory. Proceedings of the 2010 International Conference on Environmental Science and Information Application Technology, Wuhan, 17-18 July 2010, 496-499.
[22] 韦勇, 连一峰, 冯登国 (2009) 基于信息融合的网络安全态势评估模型. 计算机研究与发展, 3, 353-362.
[23] 梅海彬, 龚俭 (2011) 多IDS环境中基于可信度的警报关联方法研究. 通信学报, 4, 138-146.
[24] 陈秀珍, 郑庆华, 管晓宏, 林晨光 (2006) 层次化网络安全威胁态势量化评估方法. 软件学报, 4, 885-897.
[25] 刘丽军 (2014) 基于攻防博弈模型的层次化网络安全评估探析. 网络安全技术与应用, 8, 173-175.
[26] 陈锋, 刘德辉, 张怡, 苏金树 (2011) 基于威胁传播模型的层次化网络安全评估方法. 计算机研究与发展, 6, 945-954.
[27] Lu, J., Yang, X. and Zhang, G. (2007) Support vector machine-based multi-source multi-attribute information integration for situation assessment. Expert Systems with Application, 34, 1333-1340.
[28] 王伟 (2011) AHP和SVM组合的网络安全评估研究. 计算机仿真, 3, 182-185.
[29] Zhang, J., Wang, K. and Yue, Q. (2006) Data fusion algorithm based on functional link artificial neural networks. Proceedings of the 6th World Congress on Intelligent Control and Automation, Dalian, 21-23 June 2006, 2806-2810.
[30] Ourston, D., Matzner, S., Stump, W., et al. (2003) Applications of hidden Markov models to detecting multi-stage network attacks. Proceedings of the 36th Hawaii International Conference on System Sciences, Hawaii, 6-9 January 2003, 334-342.