基于微分流形的网络攻防效用度量方法  

Metrics for network attack and defense effectiveness based on differential manifolds

作　　者：赵小林 姜筱奕 赵晶晶 徐浩 郭煚 ZHAO Xiaolin;JIANG Xiaoyi;ZHAO Jingjing;XU Hao;GUO Jiong(School of Computer Science and Technology,Beijing Institute of Technology,Beijing 100081,China)

机构地区：[1]北京理工大学计算机学院,北京100081

出　　处：《清华大学学报（自然科学版）》2020年第5期380-385,共6页Journal of Tsinghua University(Science and Technology)

基　　金：国家重点研发计划项目(2016YFB0800700)。

摘　　要：针对网络安全的度量缺乏有效的衡量动态网络中攻防的风险的问题和存在指标较多时维度高难以计算的问题,该文提出一种网络攻防效用的度量方法,通过聚类和主成分分析对指标降维、分配权重,将指标随时间的变化嵌入到微分流形中,结合攻防效用评估网络的风险值,达到衡量网络安全的效果。以CIC2017数据集为例进行实验,结果表明:该方法可衡量动态攻防过程中产生的风险从而评估网络安全,可为网络安全度量提供一种动态的衡量方式。Network security methods lack effective metrics to measure attack risks and defense capabilities in dynamic networks, especially since they have high dimensionality and are difficult to analyze since there are many indicators. This paper presents a method to quantify network attack and defense capabilities. Clustering and principal component analyses are used to reduce the dimensionality and allocate weights to the indicator groups. These indexes are embedded in differential manifolds that change with time with the network risk evaluated based on the attack risks and defense capabilities to quantify the network security effectiveness. The CIC2017 dataset is used as an example to show that this method can indicate the attach and defense risks for dynamic networks. The results show that this method can provide a dynamic method for network security measurements.

关 键 词：网络安全度量 攻防效用 指标降维 微分流形 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]