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V. Vetriselvi

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Open access Jul 2026

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

A hierarchical federated learning framework for software-defined vehicular fog computing that combines FedNova, RBPS, and matching to enable faster model adaptation to evolving attacks and support real-time safety applications where delays above 400 ms can compromise road safety.

Devendra Singh, Dhami, Ngnassi Djami et al. · 0 citations

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