VFedA: A Vertical Federated Learning Framework with Relational Alignment for Cross-Regional False Data Injection Attack Detection in Smart Grids

Binyuan Yan, Guozhi Yang, Xin Che, Xiaohan Huang

Open source

DOI: 10.3390/s26196336
Published: 2026-10-08
Container: Sensors
Publisher: MDPI AG
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.3390/s26196336,
  title = {VFedA: A Vertical Federated Learning Framework with Relational Alignment for Cross-Regional False Data Injection Attack Detection in Smart Grids},
  author = {Binyuan Yan and Guozhi Yang and Xin Che and Xiaohan Huang},
  year = {2026},
  journal = {Sensors},
  doi = {10.3390/s26196336},
  url = {https://doi.org/10.3390/s26196336}
}

RIS

TY  - JOUR
TI  - VFedA: A Vertical Federated Learning Framework with Relational Alignment for Cross-Regional False Data Injection Attack Detection in Smart Grids
AU  - Binyuan Yan
AU  - Guozhi Yang
AU  - Xin Che
AU  - Xiaohan Huang
PY  - 2026
JO  - Sensors
DO  - 10.3390/s26196336
UR  - https://doi.org/10.3390/s26196336
ER  -

APA

Yan, B., Yang, G., Che, X., & Huang, X. (2026). VFedA: A Vertical Federated Learning Framework with Relational Alignment for Cross-Regional False Data Injection Attack Detection in Smart Grids. Sensors. https://doi.org/10.3390/s26196336

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crossref · retrieved 2026-11-06T12:30:31.187Z