文献类型：期刊文献

中文题名：基于隐马尔可夫模型的电力信息系统动态威胁定量分析

英文题名：Dynamic threat quantitative analysis of power information system based on hidden Markov model

作者：苏鹏涛[1];吴贶[2];陈孟婕[3];张雪芹[3]

机构：[1]上海欣能信息科技发展有限公司,上海200025;[2]上海挚达科技发展有限公司,上海200433;[3]华东理工大学信息科学与工程学院,上海200237

年份：2022

卷号：44

期号：4

起止页码：388

中文期刊名：上海理工大学学报

外文期刊名：Journal of University of Shanghai For Science and Technology

收录：Scopus;北大核心:【北大核心2020】；CSCD:【CSCD_E2021_2022】；

语种：中文

中文关键词：电力信息系统;威胁定量分析;隐马尔可夫;入侵报警;贝叶斯网络

外文关键词：power information system;quantitative threat analysis;hidden Markov;intrusion alarm;Bayesian network

摘要：针对典型电力信息系统的网络威胁定量评估问题,提出了基于网络入侵检测系统(network intrusion detection syetem,NIDS)报警信息和隐马尔可夫模型的网络威胁动态分析方法 HMMNIDS。该方法充分利用NIDS报警信息,从优先级、严重度、资产值和可信度4个方面分析NIDS报警信息,给出了报警威胁定量描述和分类方法,优化了隐马尔可夫模型中的观测矩阵;基于贝叶斯网络分析攻击成功的可信度,避免NIDS误警信息干扰;基于改进的隐马尔可夫模型,融合得到系统的动态风险量化值。基于Darpa2000实验场景模拟DDoS攻击,通过对比实验,验证了所提方法的有效性和优越性。
Aiming at the problem of network threat quantitative evaluation of typical power information system,a network threat dynamic analysis method hmm-ids based on network intrusion detection syetem(NIDS) alarm information and hidden Markov model was proposed in this paper.NIDS alarm information was fully used to analyzes alarm threats from four aspects:priority,severity,asset value and reliability.A quantitative description and classification method of alarm threats were given and the observation matrix in hidden Markov model was optimized.The reliability of successful attack based on Bayesian network was analyzed,which avoided the interference of NIDS false alarm information.Based on the improved hidden Markov model,the dynamic risk quantification value of the system was obtained by fusion.DDoS attacks were simulated based on DARPA2000 experimental scenario.Through comparative experiments,the effectiveness and superiority of the proposed method were verified.