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基于ARIMA预测修正的工控系统态势理解算法
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
Department工业控制网络与系统研究室
Source Publication计算机应用研究
ISSN1001-3695
2019
Volume37Issue:9Pages:1-5
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
Abstract随着工业控制系统和以太网的高度融合,传统单一的工控系统网络安全防护技术不足以应对当前严峻的工控系统安全形势。结合态势感知的概念,重点对工控系统现场控制层数据进行分析,提出一种针对工业控制系统的态势理解算法。该算法利用FCM算法实现系统正常状态空间的建模,度量出实时状态偏离正常状态的程度;此外,利用数据的时序性,通过ARIMA预测出后续时刻系统数据信息;最后使用滑动窗口技术实现对系统过去、当前和未来的数据信息融合,计算出可以表征系统实时态势的二元组,直观的呈现出系统的实时安全状况,实现当前态势理解。通过数据仿真实验,验证了算法的可执行性和有效性,该算法的输出可以为安全管理人员提供可靠的决策信息。
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.
Language中文
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/25476
Collection工业控制网络与系统研究室
Corresponding Author尚文利
Affiliation1.中国科学院沈阳自动化研究所
2.中国科学院机器人与智能制造创新研究院
3.中科院网络化控制系统重点实验室
4.中国科学院大学
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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