{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T02:08:06Z","timestamp":1773799686224,"version":"3.50.1"},"reference-count":27,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,12,4]],"date-time":"2023-12-04T00:00:00Z","timestamp":1701648000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,12,4]]},"DOI":"10.1109\/globecom54140.2023.10437623","type":"proceedings-article","created":{"date-parts":[[2024,2,26]],"date-time":"2024-02-26T19:45:36Z","timestamp":1708976736000},"page":"892-897","source":"Crossref","is-referenced-by-count":6,"title":["BlockFed: A High-Performance and Trustworthy Blockchain-Based Federated Learning Framework"],"prefix":"10.1109","author":[{"given":"Rui","family":"Ning","sequence":"first","affiliation":[{"name":"Old Dominion University,Department of CS,Norfolk,VA,USA,23529"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chonggang","family":"Wang","sequence":"additional","affiliation":[{"name":"InterDigital Inc.,Conshohocken,PA,USA,19428"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xu","family":"Li","sequence":"additional","affiliation":[{"name":"InterDigital Inc.,Conshohocken,PA,USA,19428"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Robert","family":"Gazda","sequence":"additional","affiliation":[{"name":"InterDigital Inc.,Conshohocken,PA,USA,19428"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Hongyi","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Arizona,Department of ECE,Tucson,AZ,USA,85721"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.12"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2015.40"},{"key":"ref4","article-title":"Federated learning: Strategies for improving communication efficiency","author":"Konecny","year":"2016","journal-title":"arXiv preprint"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-7908-2604-3_16"},{"key":"ref6","article-title":"On-device feder-ated learning via blockchain and its latency analysis","author":"Kim","year":"2018","journal-title":"arXiv preprint"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000263"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2020.2990686"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/BIGCOM.2019.00030"},{"key":"ref10","article-title":"Learning differentially private recurrent language models","author":"McMahan","year":"2017","journal-title":"arXiv preprint"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3072611"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.23919\/APNOMS.2019.8892848"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.001.1900658"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_2"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2019.2893266"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1080\/10618600.2014.938812"},{"issue":"5","key":"ref17","first-page":"14","volume-title":"Lenet-5, convolutional neural networks","volume":"20","author":"LeCun","year":"2015"},{"key":"ref18","volume-title":"MNIST handwritten digit database","author":"LeCun","year":"2010"},{"key":"ref19","author":"Krizhevsky","year":"2009","journal-title":"Learning multiple layers of features from tiny images"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref22","author":"Minka","year":"2000","journal-title":"Estimating a dirichlet distribution"},{"key":"ref23","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"Proceedings of the International Conference on Artificial Intelligence and Statistics (AISTATS)","author":"Bagdasaryan"},{"key":"ref24","article-title":"Dba: Distributed backdoor attacks against federated learning","volume-title":"Proceedings of the International Conference on Learning Representations (ICLR)","author":"Xie"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.29007\/21r5"},{"key":"ref26","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume":"30","author":"Blanchard","year":"2017","journal-title":"Proceedings of Advances in Neural Information Processing Systems (NeurIPS)"},{"key":"ref27","first-page":"5650","article-title":"Byzantine-robust dis-tributed learning: Towards optimal statistical rates","volume-title":"Proceedings of International Conference on Machine Learning (ICML)","author":"Yin"}],"event":{"name":"GLOBECOM 2023 - 2023 IEEE Global Communications Conference","location":"Kuala Lumpur, Malaysia","start":{"date-parts":[[2023,12,4]]},"end":{"date-parts":[[2023,12,8]]}},"container-title":["GLOBECOM 2023 - 2023 IEEE Global Communications Conference"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10436708\/10436716\/10437623.pdf?arnumber=10437623","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,1]],"date-time":"2024-03-01T01:42:01Z","timestamp":1709257321000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10437623\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,12,4]]},"references-count":27,"URL":"https:\/\/doi.org\/10.1109\/globecom54140.2023.10437623","relation":{},"subject":[],"published":{"date-parts":[[2023,12,4]]}}}