Efficient privacy-preserving federated learning under dishonest-majority setting
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Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s11432-023-3977-9.pdf
Reference5 articles.
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2. Sharma S, Xing C, Liu Y, et al. Secure and efficient federated transfer learning. In: Proceedings of IEEE International Conference on Big Data, 2019. 2569–2576
3. Girgis A M, Data D, Diggavi S, et al. Shuffled model of federated learning: privacy, accuracy and communication trade-offs. IEEE J Sel Areas Inf Theor, 2021, 2: 464–478
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5. Dong Y, Chen X, Li K, et al. Flod: oblivious defender for private byzantine-robust federated learning with dishonest-majority. In: Proceedings of European Symposium on Research in Computer Security (ESORICS’21), 2021. 497–518
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