基于数据场的网络安全风险融合模型

Network Security Risk Fusion Model Based on Data Field

针对目前网络安全风险评估中基于全局信息评估策略的不足,建立一种先局部后整体的网络安全风险融合模型。该方法在主机节点模糊评判统计分析的基础上,利用网络全局定位(GNP)实现网络拓扑的坐标化,通过对重要节点以及节点间关联性因子进行加权,然后采用数据场思想实现关联节点的风险融合。通过风险场的构建,该模型能够准确反映风险的融合规律和网络安全风险态势,为管理员提供直观的安全态势视图,方便风险阻断和策略制定。

As there are shortcomings of current network security risk evaluation based on global information,a new security risk evaluation was presented to describe network security risk fusion on the basis of data field. Based on the fuzzy evaluation and statistical analysis,a new network security risk fusion model in the risk field was implemented using GNP（Global Network Position）. Through building the risk field, our experimental results demonstrate that the model could reflect the rule of security risk fusion and the security risk situation correctly, and provide intuitionistic graph for security situation in order to block risk propagation and make security policies.