SEAR: Secure and Efficient Aggregation for Byzantine-Robust Federated Learning
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DOI: 10.1109/tdsc.2021.3093711
Abstract: Federated learning facilitates the collaborative training of a global model among distributed clients without sharing their training data. Secure aggregation, a new security primitive for federated learning, aims to preserve the confidentiality of both local… read more here.
Keywords: aggregation; federated learning; secure efficient; byzantine ... See more keywords