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。
Flight delay prediction remains an important research topic due to dynamic nature in flight operation and numerous delay factors.Dynamic data-driven application system in the control area can provide a solution to this problem.However,in order to apply the approach,a state-space flight delay model needs to be established to represent the relationship among system states,as well as the relationship between system states and input/output variables.Based on the analysis of delay event sequence in a single flight,a state-space mixture model is established and input variables in the model are studied.Case study is also carried out on historical flight delay data.In addition,the genetic expectation-maximization（EM）algorithm is used to obtain the global optimal estimates of parameters in the mixture model,and results fit the historical data.At last,the model is validated in Kolmogorov-Smirnov tests.Results show that the model has reasonable goodness of fitting the data,and the search performance of traditional EM algorithm can be improved by using the genetic algorithm.
