Data-Driven Detection of Stealthy IA Attacks in Industrial Cyber-Physical Systems via DGM Quantification

Jingzhao Chen, Bin Liu, Zhiqun Jiang

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DOI: 10.3390/s26185750
Published: 2026-09-10
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26185750,
  title = {Data-Driven Detection of Stealthy IA Attacks in Industrial Cyber-Physical Systems via DGM Quantification},
  author = {Jingzhao Chen and Bin Liu and Zhiqun Jiang},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26185750},
  url = {https://doi.org/10.3390/s26185750}
}

RIS

TY  - JOUR
TI  - Data-Driven Detection of Stealthy IA Attacks in Industrial Cyber-Physical Systems via DGM Quantification
AU  - Jingzhao Chen
AU  - Bin Liu
AU  - Zhiqun Jiang
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26185750
UR  - https://doi.org/10.3390/s26185750
ER  -

APA

Chen, J., Liu, B., & Jiang, Z. (2026). Data-Driven Detection of Stealthy IA Attacks in Industrial Cyber-Physical Systems via DGM Quantification. Sensors. https://doi.org/10.3390/s26185750

Source records

crossref · retrieved 2026-11-10T07:26:04.951Z