A hierarchical federated learning framework with FedNova, game-theoretic matching, and QKD-assisted privacy for the internet of vehicles

L. Jai Vinita, V. Vetriselvi

Open source

DOI
10.3389/frai.2026.1861374
Published
2026-07-29
Container
Frontiers in Artificial Intelligence
Publisher
Frontiers Media SA
Open access
unknown

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BibTeX

@article{allodium:10.3389/frai.2026.1861374,
  title = {A hierarchical federated learning framework with FedNova, game-theoretic matching, and QKD-assisted privacy for the internet of vehicles},
  author = {L. Jai Vinita and V. Vetriselvi},
  year = {2026},
  journal = {Frontiers in Artificial Intelligence},
  doi = {10.3389/frai.2026.1861374},
  url = {https://doi.org/10.3389/frai.2026.1861374}
}

RIS

TY  - JOUR
TI  - A hierarchical federated learning framework with FedNova, game-theoretic matching, and QKD-assisted privacy for the internet of vehicles
AU  - L. Jai Vinita
AU  - V. Vetriselvi
PY  - 2026
JO  - Frontiers in Artificial Intelligence
DO  - 10.3389/frai.2026.1861374
UR  - https://doi.org/10.3389/frai.2026.1861374
ER  - 

APA

Vinita, L. J., & Vetriselvi, V. (2026). A hierarchical federated learning framework with FedNova, game-theoretic matching, and QKD-assisted privacy for the internet of vehicles. Frontiers in Artificial Intelligence. https://doi.org/10.3389/frai.2026.1861374

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