Detecting Cyber-Attacks Against Cyber-Physical Manufacturing System: A Machining Process Invariant Approach

doi:10.1109/JIOT.2024.3358798

	Detecting Cyber-Attacks Against Cyber-Physical Manufacturing System: A Machining Process Invariant Approach
	Li, Zedong 1; Chen, Xin 1; Chen, Yuqi2 ; Li, Shijie 1; Wang, Hangyu 1; Lv, Shichao 1; Sun, Limin 1
	2024
发表期刊	IEEE INTERNET OF THINGS JOURNAL (IF:8.2[JCR-2023],9.0[5-Year])
ISSN	2372-2541
EISSN	2327-4662
卷号	PP 期号:99 页码:1-1
发表状态	已发表
DOI	10.1109/JIOT.2024.3358798
摘要	The era of the Industrial Internet of Things has led to an escalating menace of Cyber-Physical Manufacturing Systems (CPMS) to cyber-attacks. Presently, the field of intrusion detection for CPMS has significant advancements. However, current methodologies require significant costs for collecting historical data to train detection models, which are tailored to specific machining scenarios. Evolving machining scenarios in the real world challenge the adaptability of these methods. In this paper, We found that the machining code of the CPMS contains a complete machining process, which is an excellent detection basis. Therefore we propose MPI-CNC, an intrusion detection approach based on Machining Process Invariant in the machining code. Specifically, MPI-CNC automates the analysis of the machining codes to extract machining process rules and key parameter rules, which serve as essential detection rules. Then, MPI-CNC actively acquires runtime status from the CPMS and matches the detection rules to identify cyber-attacks behavior. MPI-CNC was evaluated using two FANUC CNC machine tools across ten real machining scenarios. The experiment demonstrated the exceptional adaptability capability of MPI-CNC. Furthermore, MPI-CNC showed superior accuracy in detecting cyber-attacks against CPMS compared to existing state-of-the-art detection methods while ensuring normal machining operations. IEEE
关键词	Industrial Internet of Things Cyber-Physical Manufacturing Systems Computer Numerical Control Intrusion Detection Cyber Attack Codes (symbols) Computer control systems Computer crime Crime Cyber attacks Internet of things Machining centers Network security Numerical control systems Process control Code Computer numerical control Cybe-physical manufacturing system Cyber physicals Cyber-attacks Industrial internet of thing Intrusion-Detection Numerical control
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收录类别	EI
语种	英语
出版者	Institute of Electrical and Electronics Engineers Inc.
EI入藏号	20240615487827
EI主题词	Intrusion detection
EI分类号	603.1 Machine Tools, General ; 722.3 Data Communication, Equipment and Techniques ; 723 Computer Software, Data Handling and Applications ; 723.2 Data Processing and Image Processing ; 723.5 Computer Applications ; 731.1 Control Systems ; 971 Social Sciences
原始文献类型	Article in Press
来源库	IEEE
引用统计	正在获取...
文献类型	期刊论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/349742
专题	信息科学与技术学院信息科学与技术学院_PI研究组_陈宇奇
通讯作者	Sun, Limin
作者单位	1.Institute of Information Engineering, Chinese Academy of Sciences, Beijin, China 2.School of Information Science and Technology, ShanghaiTech University, Shanghai, China
推荐引用方式 GB/T 7714	Li, Zedong,Chen, Xin,Chen, Yuqi,et al. Detecting Cyber-Attacks Against Cyber-Physical Manufacturing System: A Machining Process Invariant Approach[J]. IEEE INTERNET OF THINGS JOURNAL,2024,PP(99):1-1.
APA	Li, Zedong.,Chen, Xin.,Chen, Yuqi.,Li, Shijie.,Wang, Hangyu.,...&Sun, Limin.(2024).Detecting Cyber-Attacks Against Cyber-Physical Manufacturing System: A Machining Process Invariant Approach.IEEE INTERNET OF THINGS JOURNAL,PP(99),1-1.
MLA	Li, Zedong,et al."Detecting Cyber-Attacks Against Cyber-Physical Manufacturing System: A Machining Process Invariant Approach".IEEE INTERNET OF THINGS JOURNAL PP.99(2024):1-1.