Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. A...Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. An index system for network security equipment was established and a model based on attack tree with risk fusion was proposed to obtain the score of qualitative indices. The proposed model implements attack tree model and controlled interval and memory(CIM) model to solve the problem of quantifying qualitative indices, and thus improves the accuracy of the evaluation.展开更多
为了自主保障计算机网络的安全并对网络安全风险进行自动化评估,提出一种基于攻击图的多Agent网络安全风险评估模型(Multi-agents Risk Evaluation Model Based on Attack Graph,MREMBAG)。首先提出网络风险评估模型,设计了主从Agent的...为了自主保障计算机网络的安全并对网络安全风险进行自动化评估,提出一种基于攻击图的多Agent网络安全风险评估模型(Multi-agents Risk Evaluation Model Based on Attack Graph,MREMBAG)。首先提出网络风险评估模型,设计了主从Agent的功能架构和关联关系分析流程。利用全局攻击图生成算法,以动态数据信息作为输入,通过主从Agent协同分析并构建攻击路径。基于对目标网络的攻击路径、组件、主机、网络的风险指数、漏洞及关联风险指数的计算,获取目标网络的安全风险指标。仿真实验结果验证了该评估方法的可行性和有效性。展开更多
基金The Research of Key Technology and Application of Information Security Certification Project(No.2016YFF0204001)
文摘Network security equipment is crucial to information systems, and a proper evaluation model can ensure the quality of network security equipment. However, there is only a few models of comprehensive models nowadays. An index system for network security equipment was established and a model based on attack tree with risk fusion was proposed to obtain the score of qualitative indices. The proposed model implements attack tree model and controlled interval and memory(CIM) model to solve the problem of quantifying qualitative indices, and thus improves the accuracy of the evaluation.
文摘为了自主保障计算机网络的安全并对网络安全风险进行自动化评估,提出一种基于攻击图的多Agent网络安全风险评估模型(Multi-agents Risk Evaluation Model Based on Attack Graph,MREMBAG)。首先提出网络风险评估模型,设计了主从Agent的功能架构和关联关系分析流程。利用全局攻击图生成算法,以动态数据信息作为输入,通过主从Agent协同分析并构建攻击路径。基于对目标网络的攻击路径、组件、主机、网络的风险指数、漏洞及关联风险指数的计算,获取目标网络的安全风险指标。仿真实验结果验证了该评估方法的可行性和有效性。
