IEEE Transactions on Reliability · 2024 · 26 citations · 25 references
Aviation Internet of Things (AIoT) data sharing can create tremendous value for participants. With the development of AIoT and intelligent civil aviation, data security and privacy protection have become more prominent. To improve the data security and privacy of AIoT, and allow heterogeneous devices to participate in federated training, in this article, a blockchain-based federated knowledge distillation (BFKD) is proposed. First, federated knowledge distillation is used for knowledge transferring between clients to protect client data privacy. Second, a clustering algorithm is used to select aggregated soft labels to enhance Byzantine resistance. Finally, the consortium blockchain validates the data exchange process of federated knowledge distillation. In addition, a federated score grouping practical Byzantine fault-tolerant algorithm is proposed for improving consensus efficiency and to encourage participants to contribute more public data and honestly participate in federated training. Theoretical analysis and experimental results show that BFKD boasts high data mining performance and communication efficiency while safeguarding data privacy and security.
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Bitcoin: A Peer-to-Peer Electronic Cash System
Spongebob Squarepants · SSRN Electronic Journal · 2008 · 11.2K citations · Full text
A Blockchain-Based Decentralized Federated Learning Framework with Committee Consensus
Yuzheng Li, Chuan Chen, Nan Liu et al. · IEEE Network · 2020 · 591 citations · Full text
Bflc Framework, Blockchain Consensus Protocol, Engineering +15
Communication-efficient federated learning via knowledge distillation
Chuhan Wu, Fangzhao Wu, Lingjuan Lyu et al. · Nature Communications · 2022 · 493 citations · Full text
Artificial Intelligence, Privacy Protection, Engineering +18