Privacy-preserving Byzantine-robust federated learning via blockchain systems

• Main Authors: MIAO, Yinbin, LIU, Ziteng, LI, Hongwei, CHOO, Kim-Kwang Raymond, DENG, Robert H.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2022
• Subjects: Federated learning; poisoning attacks; fully homomorphic encryption; blockchain; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/10114
• Institution: Singapore Management University

Federated learning enables clients to train a machine learning model jointly without sharing their local data. However, due to the centrality of federated learning framework and the untrustworthiness of clients, traditional federated learning solutions are vulnerable to poisoning attacks from malici...