An Intelligent Secure Fault Classification and Identification Scheme for Mining Valuable Information in IIoT

doi:10.1109/JSYST.2024.3437185

	An Intelligent Secure Fault Classification and Identification Scheme for Mining Valuable Information in IIoT
	Zhang, Ying 1,2; Zhang, Wenyuan 3; Jiang, Xiaoyu 3; Sun, Yuzhong 2; Feng, Baiming 4; Xiong, Naixue 5; Wo, Tianyu 1,2
	2024-08-14
发表期刊	IEEE SYSTEMS JOURNAL
ISSN	1932-8184
页码	12
摘要	As a pivotal component of Industry 4.0, the Industrial Internet of Things has significantly propelled the intelligent evolution of industrial systems. However, this advancement has led to increased system complexity and scale, consequently increasing the likelihood of operational failures and potential security threats. Performing an effective analysis of log information and accurately identifying system fault categories has become a substantial challenge for system administrators. To extract valuable insights from edge device logs more efficiently and ensure system security, we propose an intelligent method for system fault detection and localization. Our approach begins with an analysis of the system's source code to extract message and fault classification templates. Subsequently, real-time preprocessing of the log stream occurs, employing techniques, such as pattern matching and statistical grouping, to construct a feature vector-matrix. The detection and identification module then discerns abnormal feature vectors, using a fast classification algorithm to categorize these anomalies and determine fault types. The proposed methodology undergoes testing on our edge cloud platform. The experimental results demonstrate that the method achieves a fault detection and localization accuracy that exceeds 98%.
关键词	Industrial Internet of Things Vectors Pattern matching Fault diagnosis Fault detection Feature extraction Source coding Abnormal detection Industrial Internet of Things (IIoT) log mining security S-Kmeans
DOI	10.1109/JSYST.2024.3437185
收录类别	SCI
语种	英语
资助项目	Ministry of Industry and Information Technology[2105-370171-07-02-860873] ; Taiji Group Corporation Innovation Fund[HT-WB-2023-0099]
WOS研究方向	Computer Science ; Engineering ; Operations Research & Management Science ; Telecommunications
WOS类目	Computer Science, Information Systems ; Engineering, Electrical & Electronic ; Operations Research & Management Science ; Telecommunications
WOS记录号	WOS:001292762700001
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/39654
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Wenyuan; Xiong, Naixue
作者单位	1.Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Beijing 100191, Peoples R China 2.Chinese Acad Sci, Inst Comp Technol, State Key Lab Comp Architecture, Beijing 100080, Peoples R China 3.Tianjin Univ, Coll Intelligence Comp, Tianjin 300350, Peoples R China 4.Northwest Normal Univ, Sch Comp Sci & Engn, Lanzhou 730070, Peoples R China 5.Sul Ross State Univ, Dept Comp Sci & Math, Alpine, TX 79830 USA
推荐引用方式 GB/T 7714	Zhang, Ying,Zhang, Wenyuan,Jiang, Xiaoyu,et al. An Intelligent Secure Fault Classification and Identification Scheme for Mining Valuable Information in IIoT[J]. IEEE SYSTEMS JOURNAL,2024:12.
APA	Zhang, Ying.,Zhang, Wenyuan.,Jiang, Xiaoyu.,Sun, Yuzhong.,Feng, Baiming.,...&Wo, Tianyu.(2024).An Intelligent Secure Fault Classification and Identification Scheme for Mining Valuable Information in IIoT.IEEE SYSTEMS JOURNAL,12.
MLA	Zhang, Ying,et al."An Intelligent Secure Fault Classification and Identification Scheme for Mining Valuable Information in IIoT".IEEE SYSTEMS JOURNAL (2024):12.