SIA OpenIR  > 工业控制网络与系统研究室
Alternative TitleSituation understanding algorithm for industrial control system based on ARIMA prediction and modification
敖建松1,2,3,4; 尚文利1,2,3,4; 赵剑明1,2,3,4; 刘贤达1,2,3,4; 尹隆1,2,3,4
Source Publication计算机应用研究
Contribution Rank1
Funding Organization国家重点研发计划项目(2018YFB2004200) ; 中科院战略性先导科技专项项目(XDC02020200) ; 国家自然科学基金资助项目(61773368)
Keyword态势感知 FCM 工业控制系统 ARIMA 态势理解
Other AbstractWith the high integration of industrial control system and Ethernet, the traditional single network security protection technology of industrial control system is not enough to cope with the current severe security situation of industrial control system. Based on the concept of situational awareness, this paper focused on the analysis of the field control layer data of industrial control system, and proposed an algorithm for situational understanding of industrial control system. The algorithm used FCM algorithm to model the normal state space of the system and measure the degree of real-time state deviating from the normal state; in addition, by using the time series nature of data, the system data information at the subsequent time was predicted by ARIMA; finally, the sliding window technology was used to realize the data information fusion of the system in the past, present and future, calculated the binary which could represent the real-time situation of the system, and visual presentation of the real-time security situation of the system, realized the real-time Situation understanding. Through data simulation experiments, the feasibility and effectiveness of the algorithm are verified. The output of the algorithm can provide reliable decision-making information for security managers.
Document Type期刊论文
Corresponding Author尚文利
Recommended Citation
GB/T 7714
敖建松,尚文利,赵剑明,等. 基于ARIMA预测修正的工控系统态势理解算法[J]. 计算机应用研究,2019,37(9):1-5.
APA 敖建松,尚文利,赵剑明,刘贤达,&尹隆.(2019).基于ARIMA预测修正的工控系统态势理解算法.计算机应用研究,37(9),1-5.
MLA 敖建松,et al."基于ARIMA预测修正的工控系统态势理解算法".计算机应用研究 37.9(2019):1-5.
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