Enhancing privacy preservation and trustworthiness for decentralized federated learning

DOI10.1016/J.INS.2023.01.130OpenAlexW4318978799MaRDI QIDQ6127142

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Publication date: 10 April 2024

Published in: Information Sciences (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.ins.2023.01.130

zbMATH Keywords

privacy-preservingtrustworthinessdecentralized federated learninggradient encryption

Mathematics Subject Classification ID

Computer science (68-XX) Operations research, mathematical programming (90-XX)

Cites Work

• Efficient proof composition for verifiable computation
• Privacy preserving multi-party computation delegation for deep learning in cloud computing
• Multiparty Computation from Somewhat Homomorphic Encryption
• How to share a secret
• A Pseudorandom Generator from any One-way Function
• Quadratic Span Programs and Succinct NIZKs without PCPs
• On the Size of Pairing-Based Non-interactive Arguments

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