[1]张淑雯,刘效武,孙雪岩. 基于多源融合的网络安全态势层次感知[J].计算机技术与发展,2016,26(10):77-82.
　ZHANG Shu-wen,LIU Xiao-wu,SUN Xue-yan. Hierarchical Awareness of Network Security Situation Based on Multi-source Fusion [J].,2016,26(10):77-82.
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 基于多源融合的网络安全态势层次感知()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
26
期数:
2016年10期
页码:
77-82
栏目:
安全与防范
出版日期:
2016-10-10

文章信息/Info

Title:
 Hierarchical Awareness of Network Security Situation Based on Multi-source Fusion

文章编号:
1673-629X（2016)10-0077-06
作者:
 张淑雯; 刘效武; 孙雪岩
 曲阜师范大学 信息科学与工程学院
Author(s):
 ZHANG Shu-wen; LIU Xiao-wu; SUN Xue-yan
关键词:
 ; 网络安全态势感知; 数据融合; 蚁群算法; 神经网络; 特征选择
Keywords:
 ; network ;  security  ; situation awareness; data fusio; ant ;  colony ;  optimization; neural network; feature selection
分类号:
TP393
文献标志码:
A
摘要:
 网络安全态势感知是近年来的一种新型安全技术，因其可以解决传统安全技术难以解决的数据源单一、虚警率高等问题，提升对全局安全状况的动态理解能力而备受关注。针对现有的研究，提出一种基于多源融合的网络安全态势层次感知模型，利用蚁群D-S证据组合规则处理多源融合问题，从而减少态势参数赋予主观性强的问题。同时，利用神经网络搜索安全事件的关键特征，降低数据维数，避免维数爆炸，提高实时性。最后采用层次化感知算法，将离散报警映射为动态威胁趋势，提升对网络安全的定量分析能力。仿真结果表明，提出的算法能够提高检测率，降低误警率，可以动态监控网络安全威胁的演化状态。
Abstract:
 In recent year,network security situation awareness is an emerging security technology and garners widespread attentions be-cause it can solve the issues that the traditional security technology difficult to deal with,such as a single data source and the high false a-larm rate,and enhance the dynamic understanding abilities for the overall security situation. For the current research,a network security situation awareness model is proposed based on multi-source fusion which utilizes ant colony D-S evidence combination rule to deal with the multi-source data fusion problem with aim of reducing the subjective dependence of situation parameters. Meanwhile,the neural net-work is applied for searching key characteristics of security events to reduce data dimension,avoid dimension explosion and improve the real-time performance. It also discusses a hierarchical awareness algorithm and can map the discrete alarms to the dynamic threats tenden-cy in order to improve the capacity of quantitative analysis for network security. The simulation shows that the proposed model and algo-rithm can improve the detection rate and decrease false alarm rate,and dynamically monitor the evolution of the network security threats.

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更新日期/Last Update: 2016-11-25