Work

Publicly Auditable Federated Learning With Privacy and Byzantine Robustness

Year: 2025

Type: article

Source: IEEE Transactions on Dependable and Secure Computing

DOI: 10.1109/tdsc.2025.3609353

Authors: Huang Zeng, Anjia Yang, Jian Weng, Min-Rong Chen, Fengjun Xiao, Zilin Liu, Yi Liu

Institutions: Jinan University, South China Normal University

Language: English

Topic: Privacy-Preserving Technologies in Data

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: closed

Funder: National Natural Science Foundation of China

Awards: G2805959026, G4365675440, 基于区块链的安全数据共享关键技术研究, G6659635434, G8066162458, G8395670599, G8825203574

OpenAlex ID: W7081952998

FWCI: 0.408

Cites: 33

Cited by: 1

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