Secure Decentralized Learning with Blockchain

arXiv:2310.07079v2 Announce Type: replace
Abstract: Federated Learning (FL) is a well-known paradigm of distributed machine learning on mobile and IoT devices, which preserves data privacy and optimizes communication efficiency. To avoid the single point of failure problem in FL, decentralized federated learning (DFL) has been proposed to use peer-to-peer communication for model aggregation, which has been considered an attractive solution for machine learning tasks on distributed personal devices. However, this process is vulnerable to attackers who share false models and …

aggregation arxiv blockchain communication cs.cr cs.lg data data privacy decentralized devices distributed efficiency failure federated federated learning iot iot devices machine machine learning mobile paradigm peer-to-peer point privacy problem single well-known