Anomaly Detection Based on Zone Partition for Security Protection of Industrial Cyber-Physical Systems
- Submitting institution
-
Queen Mary University of London
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 538
- Type
- D - Journal article
- DOI
-
10.1109/TIE.2017.2772190
- Title of journal
- IEEE Transactions on Industrial Electronics
- Article number
- -
- First page
- 4257
- Volume
- 65
- Issue
- 5
- ISSN
- 0278-0046
- Open access status
- Compliant
- Month of publication
- November
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
4
- Research group(s)
-
-
- Citation count
- 32
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- International collaborative research work with HUST, the best research group in industrial Cyber-Physical Systems (iCPS) in China. Demonstrated the anomaly intrusion detection method for security protection of iCPS, an important part of our new theory of iCPS security. Yang was invited to present the work in the IET Conference on System Safety and Cyber Security October 2018, London, UK, as a keynote ( https://tv.theiet.org/?videoid=12531 ).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
