Anomaly Detection Based on Zone Partition for Industrial Cyber-Physical Systems Security Protection.pdf (666 kB)
Anomaly detection based on zone partition for security protection of industrial cyber-physical systems
journal contribution
posted on 2017-12-08, 14:34 authored by Jun Yang, Chunjie Zhou, Shuang-Hua Yang, Haizhou Xu, Bowen HuA developing trend of traditional industrial systems is the integration of the cyber and physical domain to improve flexibility and the efficiency of supervision, management and control. But, the deep integration of these Industrial Cyber-Physical Systems (ICPSs), increases the potential for security threats. Attack detection, which forms initial protective barrier, plays an important role in overall security protection. However, most traditional methods focused on cyber information and ignored any limitations that might arise from the characteristics of the physical domain. In this paper, an anomaly detection approach based on zone partition is designed for ICPSs. In detail, initially an automated zone partition method ensuring crucial system states can be observed in more than one zone is designed. Then, methods of building zone function model which do not require any prior knowledge of the physical system are presented before analyzing the anomaly based on zone information. Finally, an experimental rig is constructed to verify the effectiveness of the proposed approach. The results demonstrate that the approach presents a high accuracy solution which also performs effectively in realtime.
Funding
This work was supported in part by National Science Foundation of China under grants 61433006 and 61272204 to author C. Zhou.
History
School
- Science
Department
- Computer Science
Published in
IEEE Transactions on Industrial ElectronicsCitation
YANG, J. ... et al, 2018. Anomaly detection based on zone partition for security protection of industrial cyber-physical systems. IEEE Transactions on Industrial Electronics, 65(5), pp. 4257-4267.Publisher
© IEEEVersion
- AM (Accepted Manuscript)
Publication date
2018Notes
© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.ISSN
0278-0046eISSN
1557-9948Publisher version
Language
- en