A digital twin and deep-learning ensemble for cyber attack detection in industrial control systems at the IoT edge.
- DOI
- 10.1038/s41598-026-53863-z
- Published
- 2026 May 22
- Container
- Scientific reports
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1038/s41598-026-53863-z,
title = {A digital twin and deep-learning ensemble for cyber attack detection in industrial control systems at the IoT edge.},
author = {Sayghe A and Alahmadi MD and Gharawi AA},
year = {2026},
journal = {Scientific reports},
doi = {10.1038/s41598-026-53863-z},
url = {https://doi.org/10.1038/s41598-026-53863-z}
}RIS
TY - JOUR TI - A digital twin and deep-learning ensemble for cyber attack detection in industrial control systems at the IoT edge. AU - Sayghe A AU - Alahmadi MD AU - Gharawi AA PY - 2026 JO - Scientific reports DO - 10.1038/s41598-026-53863-z UR - https://doi.org/10.1038/s41598-026-53863-z ER -
APA
A, S., MD, A., & AA, G. (2026). A digital twin and deep-learning ensemble for cyber attack detection in industrial control systems at the IoT edge.. Scientific reports. https://doi.org/10.1038/s41598-026-53863-z
Source records
- pubmed · retrieved 2026-09-26T02:13:12.476Z