: Federated learning (FL) is an effective solution to address the problem of data silos, where multiple clients collaborate to train a model. Model training itself consumes significant communication and computational resources, implying that significant economic compensation needs to be paid to incentivize clients to p...
Shi-Hong Wu, Zhen-Bin Guo, Yu-Chuan Luo et al.· Computers, Materials & C...· 0 citations
Lightweight authentication schemes based on pre-shared keys (PSK) are widely adopted to secure data access and preserve privacy in the Internet of Things (IoT). However, ensuring forward secrecy in the event of PSK compromise remains a fundamental challenge. Although credential update mechanisms can provide dynamic aut...
Zhen-Bin Guo, Shi-Hong Wu, Yu-Chuan Luo et al.· IEEE Transactions on Informa...· 0 citations
FedPrism is proposed, a novel framework that shifts alignment granularity from the coarse client level to the precise instance level and devise a Posterior-Guided Performance Distillation mechanism that leverages experts' actual training loss as self-supervision to autonomously refine routing policies without explicit...
Ke Wang, Shao-Jing Fu, Yu-Chuan Luo et al.· Proceedings of the Thirty-Fi...· 0 citations
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