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However, there still remain challenges to fulfilling FL with blockchain, regarding effectiveness, efficiency, and security. In this paper, we propose a new blockchain system for FL, called FedChain. To mitigate client drift and accelerate training, we present a clustered semi-asynchronous method for model aggregation. To optimize the local training in FL, we introduce a knowledge transfer method using other clients on the peer-to-peer network of blockchain. Moreover, we implement an access control mechanism to store and transmit models safely and efficiently. Extensive experiments on various benchmark datasets show that FedChain achieves superior results in accuracy, convergence, throughput, and latency.<\/jats:p>","DOI":"10.14778\/3641204.3641208","type":"journal-article","created":{"date-parts":[[2024,5,2]],"date-time":"2024-05-02T22:05:43Z","timestamp":1714687543000},"page":"966-979","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":11,"title":["A Blockchain System for Clustered Federated Learning with Peer-to-Peer Knowledge Transfer"],"prefix":"10.14778","volume":"17","author":[{"given":"Honghu","family":"Wu","sequence":"first","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangrong","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wei","family":"Hu","sequence":"additional","affiliation":[{"name":"State Key Laboratory for Novel Software Technology, Nanjing University, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2024,5,2]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Elli Androulaki Artem Barger Vita Bortnikov Christian Cachin Konstantinos Christidis Angelo De Caro David Enyeart Christopher Ferris Gennady Laventman Yacov Manevich Srinivasan Muralidharan Chet Murthy Binh Nguyen Manish Sethi Gari Singh Keith Smith Alessandro Sorniotti Chrysoula Stathakopoulou Marko Vukolic Sharon Weed Cocco and Jason Yellick. 2018. 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