摘要
传统基于贝叶斯网络攻击图的攻击路径预测方法容易产生冗余路径,节点置信度计算不够精确。为此,提出一种新的九元组攻击图模型。定义资源脆弱性指数和攻击行为风险的概念,结合攻击威胁性指数分析(ATI)方法,给出基于威胁性指数分析的攻击路径生成方法,通过将操作成本的概念引入到似然加权抽样法中,使节点置信度的计算更加精确,并尽可能避免冗余路径的产生。分析结果表明,该方法能有效减免冗余路径的产生,提高节点置信度计算结果的精度。
The traditional attack path prediction method based on Bayesian network attack graph is easy to produce redundant paths,and node confidence degree calculation is not precise enough. In order to solve these problems,this paper presents a new nine tuples attack graph model,and defines the resource vulnerability index and aggressive behavior risk. Combined with Attack Threat Index （ATI） analysis method, the attack path generation method based on threat index analysis is proposed. The concept of operating cost is introduced into the likelihood weighted sampling method to make node confidence degree calculation more precise and avoid redundant path generation. Analysis results show that the proposed method can effectively reduce the redundant path and improves the accuracy node confidence degree calculation.
出处
《计算机工程》
CAS
CSCD
北大核心
2016年第9期132-137,143,共7页
Computer Engineering
基金
国家自然科学基金资助项目(61300216)
教育部博士点基金资助项目(20124116120004)
河南省教育厅科学技术研究重点基金资助项目(13A510325)
关键词
攻击图
攻击路径
脆弱性评估
攻击威胁
似然加权抽样
attack graph
attack path
vulnerability assessment
attack threat
likelihood weighted sampling
作者简介
王辉（1975-），男，副教授，主研方向为网络安全、无线传感器网络；E-mail：wanghui_jsj@hpu．edu．cn
王腾飞，硕士研究生；
刘淑芬，教授、博士生导师。
