{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T21:45:25Z","timestamp":1743025525214,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":21,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819756056"},{"type":"electronic","value":"9789819756063"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-5606-3_17","type":"book-chapter","created":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T09:03:33Z","timestamp":1722243813000},"page":"199-207","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["When Blockchain Meets Asynchronous Federated Learning"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0009-0004-2127-2176","authenticated-orcid":false,"given":"Rui","family":"Jing","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7663-278X","authenticated-orcid":false,"given":"Wei","family":"Chen","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-1089-962X","authenticated-orcid":false,"given":"Xiaoxin","family":"Wu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zehua","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zijian","family":"Tian","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,7,30]]},"reference":[{"key":"17_CR1","unstructured":"Chui, M., Collins, M., Patel, M.: The Internet of Things: catching up to an accelerating opportunity (2021)"},{"key":"17_CR2","doi-asserted-by":"crossref","unstructured":"Toyoda, K., Zhang, A.N.: Mechanism design for an incentive-aware blockchain-enabled federated learning platform. In: Proceedings of the 2019 IEEE International Conference on Big Data (Big Data), 9\u201312 Dec. 2019 (2019)","DOI":"10.1109\/BigData47090.2019.9006344"},{"key":"17_CR3","doi-asserted-by":"crossref","unstructured":"Tang, Y.M., Zhang, Y.T., Niu, T., et al.: A survey on blockchain-based federated learning: categorization, application and analysis. Cmes-Comput. Model. Eng. Sci. (2024)","DOI":"10.32604\/cmes.2024.030084"},{"key":"17_CR4","unstructured":"Nguyen, J., Malik, K., Zhan, H., et al.: Federated learning with buffered asynchronous aggregation. In: Proceedings of the International Conference on Artificial Intelligence and Statistics, PMLR (2022)"},{"key":"17_CR5","unstructured":"Xie, C., Koyejo, S., Gupta, I., et al.: Asynchronous federated optimization (2019)"},{"key":"17_CR6","doi-asserted-by":"crossref","unstructured":"Schmid, R., Pfitzner, B., Beilharz, J., et al.: Tangle ledger for decentralized learning. In: Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium Workshops (IPDPSW). IEEE (2020)","DOI":"10.1109\/IPDPSW50202.2020.00144"},{"key":"17_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.119896","volume":"223","author":"S Ko","year":"2023","unstructured":"Ko, S., Lee, K., Cho, H., et al.: Asynchronous federated learning with directed acyclic graph-based blockchain in edge computing: overview, design, and challenges. Expert Syst. Appl. 223, 119896 (2023)","journal-title":"Expert Syst. Appl."},{"issue":"4","key":"17_CR8","doi-asserted-by":"publisher","first-page":"4298","DOI":"10.1109\/TVT.2020.2973651","volume":"69","author":"YL Lu","year":"2020","unstructured":"Lu, Y.L., Huang, X.H., Zhang, K., et al.: Blockchain empowered asynchronous federated learning for secure data sharing in internet of vehicles. IEEE Trans. Veh. Technol. 69(4), 4298\u20134311 (2020)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"1","key":"17_CR9","doi-asserted-by":"publisher","first-page":"74","DOI":"10.1109\/IOTM.001.2300092","volume":"7","author":"J Zhang","year":"2024","unstructured":"Zhang, J., Li, S.: Blockchain-empowered vehicular intelligence: a perspective of asynchronous federated learning. IEEE Internet Things Magaz. 7(1), 74\u201380 (2024)","journal-title":"IEEE Internet Things Magaz."},{"key":"17_CR10","doi-asserted-by":"publisher","first-page":"133394","DOI":"10.1109\/ACCESS.2023.3335603","volume":"11","author":"Q Zhuohao","year":"2023","unstructured":"Zhuohao, Q., Firdaus, M., Noh, S., et al.: A blockchain-based auditable semi-asynchronous federated learning for heterogeneous clients. IEEE Access 11, 133394\u2013133412 (2023)","journal-title":"IEEE Access"},{"key":"17_CR11","doi-asserted-by":"crossref","unstructured":"Gulati, M., Dadkhah, N., Gro\u00df, B., et al.: BETA-FL: Blockchain-event triggered asynchronous federated learning in supply chains. In: Proceedings of the 2023 Fifth International Conference on Blockchain Computing and Applications (BCCA), 24\u201326 Oct. 2023 (2023)","DOI":"10.1109\/BCCA58897.2023.10338891"},{"key":"17_CR12","doi-asserted-by":"crossref","unstructured":"Wang, R., Tsai, W.-T.: Asynchronous federated learning system based on permissioned blockchains 22(4), 1672 (2022)","DOI":"10.3390\/s22041672"},{"issue":"15","key":"17_CR13","doi-asserted-by":"publisher","first-page":"13281","DOI":"10.1109\/JIOT.2023.3262546","volume":"10","author":"X Yan","year":"2023","unstructured":"Yan, X., Miao, Y., Li, X., et al.: Privacy-preserving asynchronous federated learning framework in distributed IoT. IEEE Internet Things J. 10(15), 13281\u201313291 (2023)","journal-title":"IEEE Internet Things J."},{"key":"17_CR14","doi-asserted-by":"publisher","unstructured":"Tomiyama, E., Esaki, H., Ochiai, H.: Competitive and asynchronous decentralized federated learning with blockchain smart contracts. In: Proceedings of the 2023 ACM Conference on Information Technology for Social Good, pp. 92\u201399. Association for Computing Machinery, Lisbon, Portugal (2023). https:\/\/doi.org\/10.1145\/3582515.3609522","DOI":"10.1145\/3582515.3609522"},{"key":"17_CR15","unstructured":"Wang, Z., Hu, Q., et al.: Blockchain-based federated learning: a comprehensive survey (2021)"},{"key":"17_CR16","doi-asserted-by":"crossref","unstructured":"Xu, C., Qu, Y., Eklund, P.W., et al.: BAFL: an efficient blockchain-based asynchronous federated learning framework. In: Proceedings of the 2021 IEEE Symposium on Computers and Communications (ISCC), 5\u20138 Sept. 2021 (2021)","DOI":"10.1109\/ISCC53001.2021.9631405"},{"key":"17_CR17","doi-asserted-by":"crossref","unstructured":"Li, Q., Gong, B., Zhu, Y., et al.: Research on decentralized federated learning system for vehicle data privacy protection based on blockchain. In: Proceedings of the 2023 IEEE International Conference on Image Processing and Computer Applications (ICIPCA), 11\u201313 Aug. 2023 (2023)","DOI":"10.1109\/ICIPCA59209.2023.10257765"},{"issue":"5","key":"17_CR18","doi-asserted-by":"publisher","first-page":"6584","DOI":"10.1109\/TVT.2022.3232603","volume":"72","author":"C Xu","year":"2023","unstructured":"Xu, C., Qu, Y., Luan, T.H., et al.: An efficient and reliable asynchronous federated learning scheme for smart public transportation. IEEE Trans. Veh. Technol. 72(5), 6584\u20136598 (2023)","journal-title":"IEEE Trans. Veh. Technol."},{"issue":"5","key":"17_CR19","doi-asserted-by":"publisher","first-page":"1092","DOI":"10.1109\/TC.2021.3072033","volume":"71","author":"L Feng","year":"2022","unstructured":"Feng, L., Zhao, Y., Guo, S., et al.: BAFL: a blockchain-based asynchronous federated learning framework. IEEE Trans. Comput. 71(5), 1092\u20131103 (2022)","journal-title":"IEEE Trans. Comput."},{"key":"17_CR20","doi-asserted-by":"crossref","unstructured":"Huang, X., Deng, X., Chen, Q., et al.: AFLChain: blockchain-enabled asynchronous federated learning in edge computing network. In: Proceedings of the 2023 IEEE 97th Vehicular Technology Conference (VTC2023-Spring), 20\u201323 June 2023 (2023)","DOI":"10.1109\/VTC2023-Spring57618.2023.10199280"},{"key":"17_CR21","doi-asserted-by":"crossref","unstructured":"Shrestha, A.K., Khan, F.A., Shaikh, M.A., et al.: Enhancing scalability and reliability in semi-decentralized federated learning with blockchain: trust penalization and asynchronous functionality. In: 2023 IEEE 14th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), pp. 0230\u20130236. IEEE (2023)","DOI":"10.1109\/UEMCON59035.2023.10316006"}],"container-title":["Lecture Notes in Computer Science","Advanced Intelligent Computing Technology and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-5606-3_17","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,7,29]],"date-time":"2024-07-29T09:07:18Z","timestamp":1722244038000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-5606-3_17"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819756056","9789819756063"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-5606-3_17","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"30 July 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this paper.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"ICIC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Tianjin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"5 August 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8 August 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icic2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ic-icc.cn\/2024\/index.htm","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}