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Dec 7, 2020 · Abstract: Federated learning (FL) enables a large number of clients to collaboratively train a global model through sharing their gradients ...
Aug 18, 2022 · Abstract. This work addresses the security flaw in the original VeriFL protocol and proposes a patched protocol.
This repository provides two IntelliJ IDEA projects for VeriFL. The project Client involves the Android benchmark for clients participating in VeriFL protocol.
May 31, 2021 · Federated learning (FL) enables a large number of clients to collaboratively train a global model through sharing their gradients in each ...
Abstract—Federated learning (FL) enables a large number of clients to collaboratively train a global model through sharing.
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Abstract—Federated learning (FL) enables a large number of clients to collaboratively train a global model through sharing.
Fixing Issues and Achieving Maliciously Secure Verifiable Aggregation in "VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning ...
This paper proposes an effective secure aggregation verifiable federated learning scheme, which has both high communication efficiency and privacy protection ...
VeriFL: Communication-efficient and fast verifiable aggregation for federated learning. IEEE Transactions on Information. Forensics and Security, 16:1736–1751, ...
Jul 21, 2023 · This paper proposes an effective secure aggregation verifiable federated learning scheme, which has both high communication efficiency and ...