Enhancing Mutual Trustworthiness in Federated Learning for Data-Rich Smart Cities

Federated learning is a promising collaborative and privacy-preserving machine learning approach in data-rich smart cities. Nevertheless, the inherent heterogeneity of these urban environments presents a significant challenge in selecting trustworthy clients for collaborative model training. The usa...

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Veröffentlicht in:	IEEE internet of things journal 2024-10, p.1-1
Hauptverfasser:	Wehbi, Osama, Arisdakessian, Sarhad, Guizani, Mohsen, Wahab, Omar Abdel, Mourad, Azzam, Otrok, Hadi, khzaimi, Hoda Al, Ouni, Bassem
Format:	Artikel
Sprache:	eng
Schlagworte:	Bootstrapping Data privacy Federated learning Game theory Internet of Things IoT Performance evaluation Recommendation Systems Reliability Servers Smart cities Smart devices Training Trustworthiness
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