{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T12:02:50Z","timestamp":1775563370855,"version":"3.50.1"},"reference-count":16,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,3,3]],"date-time":"2026-03-03T00:00:00Z","timestamp":1772496000000},"content-version":"vor","delay-in-days":61,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Procedia Computer Science"],"published-print":{"date-parts":[[2026]]},"DOI":"10.1016\/j.procs.2026.03.021","type":"journal-article","created":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T12:39:40Z","timestamp":1774355980000},"page":"533-540","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"special_numbering":"C","title":["A Blockchain-based Federated Learning Implementation Within a Recommendation System Landscape"],"prefix":"10.1016","volume":"278","author":[{"given":"Jo\u00e3o","family":"Gaspar","sequence":"first","affiliation":[]},{"given":"Jos\u00e9","family":"Pessoa","sequence":"additional","affiliation":[]},{"given":"Bruno","family":"Ribeiro","sequence":"additional","affiliation":[]},{"given":"Diogo","family":"Martinho","sequence":"additional","affiliation":[]},{"given":"Joaquim","family":"Santos","sequence":"additional","affiliation":[]},{"given":"Goreti","family":"Marreiros","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"key":"10.1016\/j.procs.2026.03.021_bib1","series-title":"\u201cInverting Gradients - How Easy Is It to Break Privacy in Federated Learning?\u201d Advances in Neural Information Processing Systems 33: 16937\u201316947","author":"Geiping","year":"2020"},{"issue":"1","key":"10.1016\/j.procs.2026.03.021_bib2","doi-asserted-by":"crossref","first-page":"2618","DOI":"10.1109\/TCE.2023.3318754","article-title":"\u201cFederated Learning-Based Personalized Recommendation Systems: An Overview on Security and Privacy Challenges.\u201d","volume":"70","author":"Javeed","year":"2024","journal-title":"IEEE Transactions on Consumer Electronics"},{"issue":"4","key":"10.1016\/j.procs.2026.03.021_bib3","doi-asserted-by":"crossref","first-page":"3347","DOI":"10.1109\/TKDE.2021.3124599","article-title":"\u201cA Survey on Federated Learning Systems: Vision, Hype and Reality for Data Privacy and Protection.\u201d","volume":"35","author":"Li","year":"2023","journal-title":"IEEE Transactions on Knowledge and Data Engineering"},{"issue":"2","key":"10.1016\/j.procs.2026.03.021_bib4","doi-asserted-by":"crossref","first-page":"513","DOI":"10.1007\/s13042-022-01647-y","article-title":"\u201cA Survey on Federated Learning: Challenges and Applications.\u201d","volume":"14","author":"Wen","year":"2023","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"10.1016\/j.procs.2026.03.021_bib5","doi-asserted-by":"crossref","unstructured":"Zhang, Chen, Yu Xie, Hang Bai, Bin Yu, Weihong Li, and Yuan Gao. (2021) \u201cA Survey on Federated Learning.\u201d Knowledge-Based Systems 216: 106775. https:\/\/doi.org\/10.1016\/j.knosys.2021.106775","DOI":"10.1016\/j.knosys.2021.106775"},{"issue":"11","key":"10.1016\/j.procs.2026.03.021_bib6","doi-asserted-by":"crossref","first-page":"19188","DOI":"10.1109\/JIOT.2024.3376548","article-title":"\u201cFederated Learning With Non-IID Data: A Survey.\u201d","volume":"11","author":"Lu","year":"2024","journal-title":"IEEE Internet of Things Journal"},{"key":"10.1016\/j.procs.2026.03.021_bib7","doi-asserted-by":"crossref","first-page":"38","DOI":"10.1016\/j.comcom.2024.04.024","article-title":"\u201cPrivacy-Preserving in Blockchain-Based Federated Learning Systems.\u201d","volume":"222","author":"Sameera","year":"2024","journal-title":"Computer Communications"},{"key":"10.1016\/j.procs.2026.03.021_bib8","unstructured":"Rodeck, David, and Benjamin Curry. (2022) \u201cWhat Is Blockchain.\u201d Forbes."},{"key":"10.1016\/j.procs.2026.03.021_bib9","doi-asserted-by":"crossref","first-page":"401","DOI":"10.1016\/j.future.2023.02.008","article-title":"\u201cBlockchain for the Metaverse: A Review.\u201d","volume":"143","author":"Huynh-The","year":"2023","journal-title":"Future Generation Computer Systems"},{"issue":"5","key":"10.1016\/j.procs.2026.03.021_bib10","doi-asserted-by":"crossref","first-page":"3951","DOI":"10.1007\/s10462-022-10271-9","article-title":"\u201cSecuring Federated Learning With Blockchain: A Systematic Literature Review.\u201d","volume":"56","author":"Qammar","year":"2023","journal-title":"Artificial Intelligence Review"},{"key":"10.1016\/j.procs.2026.03.021_bib11","doi-asserted-by":"crossref","unstructured":"Zhu, Juncen, Jiannong Cao, Divya Saxena, Shan Jiang, and Houda Ferradi. (2023) \u201cBlockchain-Empowered Federated Learning: Challenges, Solutions, and Future Directions.\u201d ACM Computing Surveys 55 (11): 240. https:\/\/doi.org\/10.1145\/3570953","DOI":"10.1145\/3570953"},{"key":"10.1016\/j.procs.2026.03.021_bib12","doi-asserted-by":"crossref","unstructured":"Qu, Youyang, Md Palash Uddin, Chenquan Gan, Yong Xiang, Longxiang Gao, and John Yearwood. (2022) \u201cBlockchain-Enabled Federated Learning: A Survey.\u201d ACM Computing Surveys 55 (4): 70. https:\/\/doi.org\/10.1145\/3524104","DOI":"10.1145\/3524104"},{"key":"10.1016\/j.procs.2026.03.021_bib13","doi-asserted-by":"crossref","unstructured":"Zangerle, Eva, and Christine Bauer. (2022) \u201cEvaluating Recommender Systems: Survey and Framework.\u201d ACM Computing Surveys 55 (8): 170. https:\/\/doi.org\/10.1145\/3556536","DOI":"10.1145\/3556536"},{"key":"10.1016\/j.procs.2026.03.021_bib14","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.ins.2022.04.027","article-title":"\u201cFederated Against the Cold: A Trust-Based Federated Learning Approach to Counter the Cold Start Problem in Recommendation Systems.\u201d","volume":"601","author":"Wahab","year":"2022","journal-title":"Information Sciences"},{"key":"10.1016\/j.procs.2026.03.021_bib15","doi-asserted-by":"crossref","unstructured":"Khan, Qazi Waqas, Anam Khan, Atif Rizwan, Rashid Ahmad, Salabat Khan, and Do Kim. (2023) \u201cDecentralized Machine Learning Training: A Survey on Synchronization, Consolidation, and Topologies.\u201d IEEE Access PP: 1\u20131. https:\/\/doi.org\/10.1109\/ACCESS.2023.3284976","DOI":"10.1109\/ACCESS.2023.3284976"},{"key":"10.1016\/j.procs.2026.03.021_bib16","doi-asserted-by":"crossref","unstructured":"Gaspar, Jo\u00e3o, Jos\u00e9 Pessoa, Bruno Ribeiro, Diogo Martinho, Joaquim Santos, and Goreti Marreiros. (2025) \u201cSecurity-Enhancing Mechanisms to Strengthen Privacy on Federated Learning Based Recommendation Systems.\u201d 2025 International Workshop on Intelligent Systems (IWIS): 1\u20136. https:\/\/doi.org\/10.1109\/IWIS66215.2025.11142401","DOI":"10.1109\/IWIS66215.2025.11142401"}],"container-title":["Procedia Computer Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926006137?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S1877050926006137?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,4,7]],"date-time":"2026-04-07T11:18:27Z","timestamp":1775560707000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S1877050926006137"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":16,"alternative-id":["S1877050926006137"],"URL":"https:\/\/doi.org\/10.1016\/j.procs.2026.03.021","relation":{},"ISSN":["1877-0509"],"issn-type":[{"value":"1877-0509","type":"print"}],"subject":[],"published":{"date-parts":[[2026]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"A Blockchain-based Federated Learning Implementation Within a Recommendation System Landscape","name":"articletitle","label":"Article Title"},{"value":"Procedia Computer Science","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.procs.2026.03.021","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 The Author(s). Published by Elsevier B.V.","name":"copyright","label":"Copyright"}]}}