most citedAHSecAgg and TSKG: Lightweight Secure Aggregation for Federated Learning Without Compromise

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cs.CR2023★ 2 cited

AHSecAgg and TSKG: Lightweight Secure Aggregation for Federated Learning Without Compromise

Siqing Zhang, Yong Liao, Pengyuan Zhou

Leveraging federated learning (FL) to enable cross-domain privacy-sensitive data mining represents a vital breakthrough to accomplish privacy-preserving learning. However, attacker…

cs.CR2023

λ-SecAgg: Partial Vector Freezing for Lightweight Secure Aggregation in Federated Learning

Siqing Zhang, Yong Liao, Pengyuan Zhou

Secure aggregation of user update vectors (e.g. gradients) has become a critical issue in the field of federated learning. Many Secure Aggregation Protocols (SAPs) face exorbitant…