@inproceedings{5bff35a1ec014c559557fbaf45bdd602,
title = "Decentralized Federated Learning with Enhanced Privacy Preservation",
abstract = "We present a decentralized federated learning (FL) framework based on blockchain. In traditional federated learning, it is necessary that a third-party centralized server aggregates all the gradients which participant in the upload, but such a trusted third-party may not always exist. We address this issue with the decentralized blockchain and encrypt the neural network model parameters and gradients.",
keywords = "Federated learning, blockchain",
author = "Tseng, {Sheng Po} and Lin, {Jan Yue} and Cheng, {Wei Chien} and Yeh, {Lo Yao} and Shen, {Chih Ya}",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 2022 IEEE International Conference on Multimedia and Expo Workshops, ICMEW 2022 ; Conference date: 18-07-2022 Through 22-07-2022",
year = "2022",
doi = "10.1109/ICMEW56448.2022.9859507",
language = "???core.languages.en_GB???",
series = "ICMEW 2022 - IEEE International Conference on Multimedia and Expo Workshops 2022, Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "ICMEW 2022 - IEEE International Conference on Multimedia and Expo Workshops 2022, Proceedings",
}