{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T15:57:59Z","timestamp":1778255879629,"version":"3.51.4"},"reference-count":60,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"PCL","award":["PCL2021A02"],"award-info":[{"award-number":["PCL2021A02"]}]},{"name":"PCL","award":["PCL2021A09"],"award-info":[{"award-number":["PCL2021A09"]}]},{"name":"PCL","award":["PCL2022A03"],"award-info":[{"award-number":["PCL2022A03"]}]},{"name":"National Key R & D Program of China","award":["2020YFB1006003"],"award-info":[{"award-number":["2020YFB1006003"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172119"],"award-info":[{"award-number":["62172119"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Guangxi Natural Science Foundation","award":["2019GXNSFGA245004"],"award-info":[{"award-number":["2019GXNSFGA245004"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. on Mobile Comput."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tmc.2022.3219485","type":"journal-article","created":{"date-parts":[[2022,11,4]],"date-time":"2022-11-04T17:25:18Z","timestamp":1667582718000},"page":"850-864","source":"Crossref","is-referenced-by-count":35,"title":["SVFL: Efficient Secure Aggregation and Verification for Cross-Silo Federated Learning"],"prefix":"10.1109","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7961-5750","authenticated-orcid":false,"given":"Fucai","family":"Luo","sequence":"first","affiliation":[{"name":"Department of New Networks, Peng Cheng Laboratory, Shenzhen, Guangdong Province, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4402-7710","authenticated-orcid":false,"given":"Saif","family":"Al-Kuwari","sequence":"additional","affiliation":[{"name":"College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3571-7576","authenticated-orcid":false,"given":"Yong","family":"Ding","sequence":"additional","affiliation":[{"name":"Guangxi Key Laboratory of Cryptography and Information Security, School of Computer Science and Information Security, Guilin University of Electronic Technology, Guilin, China"}]}],"member":"263","reference":[{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-96884-1_20"},{"key":"ref6","article-title":"Safer: Sparse secure aggregation for federated learning","author":"Beguier","year":"2020"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417885"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-48000-7_36"},{"key":"ref10","article-title":"Communication-computation efficient secure aggregation for federated learning","author":"Choi","year":"2020"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1976.1055638"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.101824"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1038\/s41746-021-00431-6"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1561\/0400000042"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/spw53761.2021.00017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2660267.2660366"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3036166"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-13013-7_9"},{"key":"ref19","first-page":"201","article-title":"Cryptonets: Applying neural networks to encrypted data with high throughput and accuracy","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Gilad-Bachrach"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1017\/cbo9780511721656"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.3043139"},{"key":"ref22","first-page":"1737","article-title":"Deep learning with limited numerical precision","volume-title":"Proc. 32nd Int. Conf. Mach. Learn.","author":"Gupta"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761267"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1997.9.8.1735"},{"key":"ref25","article-title":"FastSecAgg: Scalable secure aggregation for privacy-preserving federated learning","author":"Kadhe","year":"2020"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-0186-1"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/comst.2021.3090430"},{"key":"ref28","first-page":"101","article-title":"Adam: A method for stochastic optimization","volume-title":"Proc. 3rd Int. Conf. Learn. Representations","author":"Kingma"},{"key":"ref29","article-title":"Federated learning: Strategies for improving communication efficiency","author":"Konecn\u00fd","year":"2016"},{"key":"ref30","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref31","first-page":"1106","article-title":"ImageNet classification with deep convolutional neural networks","volume-title":"Proc. Adv. Neural Informat. Process. Syst. 26th Annu. Conf. Neural Informat. Process. Syst.","author":"Krizhevsky"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1038\/srep12760"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.2002.807285"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1002\/int.22818"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-73103-8_34"},{"key":"ref36","article-title":"Federated learning of deep networks using model averaging","author":"McMahan","year":"2016"},{"key":"ref37","first-page":"35","article-title":"ABY3: A mixed protocol framework for machine learning","volume-title":"Proc. ACM SIGSAC Conf. Comput. Commun. Secur.","author":"Mohassel"},{"key":"ref38","article-title":"Multiparty homomorphic encryption: From theory to practice","volume":"2020","author":"Mouchet","year":"2020","journal-title":"IACR Cryptol. ePrint Arch."},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-49896-5_26"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICDCS.2019.00080"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-48910-X_16"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.3390\/app12020734"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2020.24202"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1080\/01611190008984249"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/359340.359342"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/GLOCOM.2018.8647927"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24119"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/359168.359176"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1038\/s41598-020-69250-1"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/JSAIT.2021.3054610"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3338501.3357370"},{"key":"ref54","article-title":"SecureNN: Efficient and private neural network training","volume":"2018","author":"Wagh","year":"2018","journal-title":"IACR Cryptol. ePrint Arch."},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2021-0011"},{"key":"ref56","article-title":"Fashion-MNIST: A novel image dataset for benchmarking machine learning algorithms","author":"Xiao","year":"2017"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2929409"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3186739"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1145\/3338501.3357371"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1982.45"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2010.73"},{"key":"ref63","first-page":"493","article-title":"Batchcrypt: Efficient homomorphic encryption for cross-silo federated learning","volume-title":"Proc. USENIX Annu. Tech. Conf.","author":"Zhang"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/tmc.2022.3148263"}],"container-title":["IEEE Transactions on Mobile Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7755\/10345399\/09939096.pdf?arnumber=9939096","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,19]],"date-time":"2023-12-19T17:15:03Z","timestamp":1703006103000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9939096\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":60,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tmc.2022.3219485","relation":{"has-preprint":[{"id-type":"doi","id":"10.36227\/techrxiv.19428755.v1","asserted-by":"object"},{"id-type":"doi","id":"10.36227\/techrxiv.19428755","asserted-by":"object"}]},"ISSN":["1536-1233","1558-0660","2161-9875"],"issn-type":[{"value":"1536-1233","type":"print"},{"value":"1558-0660","type":"electronic"},{"value":"2161-9875","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}