留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

构建广义立方体感知网络安全态势

文志诚 陈志刚

文志诚, 陈志刚. 构建广义立方体感知网络安全态势[J]. 北京航空航天大学学报, 2015, 41(10): 1966-1974. doi: 10.13700/j.bh.1001-5965.2015.0010
引用本文: 文志诚, 陈志刚. 构建广义立方体感知网络安全态势[J]. 北京航空航天大学学报, 2015, 41(10): 1966-1974. doi: 10.13700/j.bh.1001-5965.2015.0010
WEN Zhicheng, Chen Zhigang. Constructing general cube to be aware of network security situation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1966-1974. doi: 10.13700/j.bh.1001-5965.2015.0010(in Chinese)
Citation: WEN Zhicheng, Chen Zhigang. Constructing general cube to be aware of network security situation[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1966-1974. doi: 10.13700/j.bh.1001-5965.2015.0010(in Chinese)

构建广义立方体感知网络安全态势

doi: 10.13700/j.bh.1001-5965.2015.0010
基金项目: 国家自然科学基金(61073186,61073104,60903058);中南大学博士后基金
详细信息
    作者简介:

    文志诚(1972-),男,湖南东安人,副教授,zcwen@mail.shu.edu.cn

    通讯作者:

    陈志刚(1964-),男,湖南益阳人,教授,czg@mail.csu.edu.cn,主要研究方向为网络计算与分布式处理.

  • 中图分类号: TP311

Constructing general cube to be aware of network security situation

  • 摘要: 针对大多方法感知范围局限、信息来源单一、空间时间复杂性高及准确性偏差较大等问题,提出了分层感知模型与构建广义立方体感知网络安全态势的方法.将监测到的连续型态势因子数据经"3σ法则"离散化预处理后,聚合在所构建的广义立方体格中,纵向上融合成组件的安全态势,横向上对组件安全态势采用统计的方法融合成网络的安全态势,为增强网络安全性提供可靠的参照依据.利用网络实例数据对所提出的网络安全态势感知模型和算法进行验证,表明了该方法的正确性.

     

  • [1] Bass T.Multi-sensor data fusion for next generation distributed intrusion detection systems[C]∥Proceedings of the'99 IRIS National Symposium on Sensor and Data Fusion.Piscataway,NJ:IEEE Press,1999:24-27.
    [2] Mazur J,Kaderali L.The importance and challenges of bayesian parameter learning in systems biology[J].Model Based Parameter Estimation Contributions in Mathematical and Computational Sciences,2013,4:145-156.
    [3] 黄同庆,庄毅.一种实时网络安全态势预测方法[J].小型微型计算机系统,2014,35(2):303-306.Huang T Q,Zhuang Y.An approach to real-time network security situation prediction[J].Journal of Chinese Computer Systems,2014,35(2):303-306(in Chinese).
    [4] Blasch E P,Plano S.JDL level 5 fusion model "user refinement" issues and applications in group tracking[C]∥Proceedings of the Signal Processing,Sensor Fusion,and Target Recognition XI,Spie.Bellingham,WA:SPIE,2002:270-279.
    [5] 龚正虎,卓莹.网络态势感知研究[J].软件学报,2010,21(7):1605-1619.Gong Z H,Zhuo Y.Research on cyberspace situational awareness[J].Journal of Software,2010,21(7):1605-1619(in Chinese).
    [6] Bradshaw J M,Carvalho M,Bunch L,et al.Sol:An agent-based framework for cyber situation awareness[J].KI-Künstliche Intelligenz,2012,26(1):127-140.
    [7] Digioia G,Foglietta C,Oliva G,et al.Aware online interdependency modeling via evidence theory[J].International Journal of Critical Infrastructures,2013,6893:74-92.
    [8] Bazan J G,Bazan-Socha S,Buregwa-Czuma S,et al.Classifiers based on data sets and domain knowledge:A rough set approach[J].Intelligent Systems Reference Library,2013,43:93-136.
    [9] Sample C,Schaffer K.An overview of anomaly detection[J].IT Professional,2013,15(1):8-11.
    [10] 王宏,龚正虎.一种基于信息熵的关键流量矩阵发现算法[J].软件学报,2009,20(5):1377-1383.Wang H,Gong Z H.Algorithm based on entropy for finding critical traffic matrices[J].Journal of Software,2009,20(5):1377-1383(in Chinese).
    [11] 陈秀真,郑庆华,管晓宏,等.层次化网络安全威胁态势量化评估方法[J].软件学报,2006,17(4):885-897.Chen X Z,Zheng Q H,Guan X H,et al.Quantitative hierarchical threat evaluation model for network security[J].Journal of Software,2006,17(4):885-897(in Chinese).
    [12] Görnitz N,Kloft M,Rieck K,et al.Toward supervised anomaly detection[J].Journal of Artificial Intelligence Research,2013,46:235-262.
    [13] Erbachera R F,Frinckeb D A,Wongb P C,et al.A multi-phase network situational awareness cognitive task analysis[J].Information Visualization,2010,9(3):204-219.
    [14] 韦勇,连一峰,冯登国.基于信息融合的网络安全态势评估模型[J].计算机研究与发展,2009,46(3):353-362.Wei Y,Lian Y F,Feng D G.A network security situational awareness model based on information fusion[J].Journal of Computer Research and Development,2009,46(3):353-362(in Chinese).
    [15] 张勇,谭小彬,崔孝林,等.基于Markov博弈模型的网络安全态势感知方法[J].软件学报,2011,22(3):495-508.Zhang Y,Tan X B,Cui X L,et al.Network security situation awareness approach based on Markov game model[J].Journal of Software,2011,22(3):495-508(in Chinese).
    [16] 谢丽霞,王亚超,于巾博.基于神经网络的网络安全态势感知[J].清华大学学报:自然科学版,2013,53(12):1750-1760.Xie L X,Wang Y C,Yu J B.Network security situation awareness based on neural networks[J].Journal of Tsinghua University:Science & Technology,2013,53(12):1750-1760(in Chinese).
  • 加载中
计量
  • 文章访问数:  708
  • HTML全文浏览量:  52
  • PDF下载量:  473
  • 被引次数: 0
出版历程
  • 收稿日期:  2015-01-05
  • 修回日期:  2015-04-10
  • 网络出版日期:  2015-10-20

目录

    /

    返回文章
    返回
    常见问答