PFLM: privacy-preserving federated learning with membership proof

DOI10.1016/j.ins.2021.05.077OpenAlexW3167626677MaRDI QIDQ6066136

Changsong Jiang, Chunxiang Xu, Yuan Zhang

Publication date: 12 December 2023

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

Full work available at URL: https://doi.org/10.1016/j.ins.2021.05.077

zbMATH Keywords

machine learningprivacy-preservingfederated learningmembership proof

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Cryptography (94A60)

Cites Work

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• Blind Schnorr signatures and signed ElGamal encryption in the algebraic group model
• The Bitcoin Backbone Protocol: Analysis and Applications
• How to share a secret
• Large-Scale Machine Learning with Stochastic Gradient Descent
• How to Generate Cryptographically Strong Sequences of Pseudorandom Bits
• A public key cryptosystem and a signature scheme based on discrete logarithms
• New directions in cryptography
• Separating IND-CPA and Circular Security for Unbounded Length Key Cycles
• Public Key Cryptography - PKC 2006

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