计算机科学 ›› 2011, Vol. 38 ›› Issue (Z10): 30-35.

• 信息安全 • 上一篇    下一篇

面向大规模网络的安全态势实时量化感知模型

郑黎明,邹鹏,张建锋,贾焰,韩伟红   

  1. (国防科技大学计算机学院 长沙410073) (装备指挥技术学院 北京100029)
  • 出版日期:2018-11-16 发布日期:2018-11-16
  • 基金资助:
    本文受国家高技术研究发展计划(863,2011AA010702)资助。

Real Time Situational Awareness Model for Large-scale Networks

ZHENG Li-ming,ZOU Peng,ZHANG Jian-feng,JIA Yan,HAN Wei-hong   

  • Online:2018-11-16 Published:2018-11-16

摘要: 网络安全态势感知能够实时发现潜在的网络风险,对提高网络的应急响应和主动防御能力起着重要的作用。现有的各种态势感知算法在规模上和时间上都不能适应大规模网络实时态势感知的要求,提出了基于指标体系的实时大规模网络安全态势量化感知模型,首先建立了层次化的指标体系,通过数据融合、关联分析等方法对网络安全日志数据进行处理,再针对各个属性采用不同的量化方法,将其聚集成综合网络安全态势指数。最后通过系统实际部署运行过程中的两个案例对所提出的网络安全态势感知模型和算法进行实例分析,结果证明了所提模型和算法的有效性和合理性。

关键词: 网络安全,指数,指标体系,态势感知

Abstract: NSAS (Network Situation Awareness System) can identify and predict potential attacks. It plays an important role in improving the emergency response capacity and proactive defense capability of the networks. Existing NSASs have many faults, such as lacking for multi source information, higher computational complexity, which arc difficult to be applied to larg}scale networks and real-time situational awareness. This paper introduced an NSAS for largescale network. The situational awareness model was proposed first, and then the details of key technologies, including data fusion, correlation analysis, index quantification and event predication,were given. I}he experimental results demonstrate the effectiveness and reasonability of the proposed model.

Key words: Network security, Index, Index system, Situation awareness

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