{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:40:40Z","timestamp":1773247240279,"version":"3.50.1"},"reference-count":60,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"17","license":[{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,9,1]],"date-time":"2024-09-01T00:00:00Z","timestamp":1725148800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"CCF-Phytium Fund","award":["CCF-Phytium 202306"],"award-info":[{"award-number":["CCF-Phytium 202306"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21B2021"],"award-info":[{"award-number":["U21B2021"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2024,9,1]]},"DOI":"10.1109\/jiot.2024.3405939","type":"journal-article","created":{"date-parts":[[2024,5,27]],"date-time":"2024-05-27T17:23:04Z","timestamp":1716830584000},"page":"28774-28786","source":"Crossref","is-referenced-by-count":12,"title":["Client-Side Gradient Inversion Attack in Federated Learning Using Secure Aggregation"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3206-9515","authenticated-orcid":false,"given":"Yu","family":"Sun","sequence":"first","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-6272-7879","authenticated-orcid":false,"given":"Zheng","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6441-5729","authenticated-orcid":false,"given":"Jian","family":"Cui","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0113-2182","authenticated-orcid":false,"given":"Jianhua","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8285-6077","authenticated-orcid":false,"given":"Kailang","family":"Ma","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2965-3518","authenticated-orcid":false,"given":"Jianwei","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Beihang University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","first-page":"1273","article-title":"Communication-efficient learning of deep networks from decentralized data","volume-title":"Proc. Artif. Intell. Stat.","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_17"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3325822"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00029"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE51399.2021.00023"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref7","first-page":"1964","article-title":"Label-only membership inference attacks","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","author":"Choquette-Choo"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134012"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_2"},{"key":"ref11","first-page":"16937","article-title":"Inverting gradients-how easy is it to break privacy in federated learning?","volume-title":"Proc. 34th Adv. Neural Inf. Process. Syst.","author":"Geiping"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01607"},{"key":"ref13","first-page":"29898","article-title":"Gradient inversion with generative image prior","volume-title":"Proc. 35th Adv. Neural Inf. Process. Syst.","author":"Jeon"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00989"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/SPW53761.2021.00017"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2022.3201231"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417885"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3338466.3358926"},{"key":"ref20","first-page":"493","article-title":"BatchCrypt: Efficient homomorphic encryption for cross-silo federated learning","volume-title":"Proc. USENIX Annu. Tech. Conf. (USENIX ATC)","author":"Zhang"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3323358"},{"key":"ref22","article-title":"signSGD with majority vote is communication efficient and fault tolerant","author":"Bernstein","year":"2019","journal-title":"arXiv:1810.05291"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.5555\/3294771.3294915"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00495"},{"key":"ref25","first-page":"3174","article-title":"Adaptive gradient quantization for data-parallel SGD","volume-title":"Proc. 34th Adv. Neural Inf. Process. Syst.","author":"Faghri"},{"key":"ref26","article-title":"NUQSGD: Improved communication efficiency for data-parallel SGD via nonuniform quantization","author":"Ramezani-Kebrya","year":"2021","journal-title":"arXiv:1908.06077"},{"key":"ref27","article-title":"iDLG: Improved deep leakage from gradients","author":"Zhao","year":"2020","journal-title":"arXiv:2001.02610"},{"key":"ref28","first-page":"1","article-title":"Instance-wise batch label restoration via gradients in federated learning","volume-title":"Proc. 11th Int. Conf. Learn. Represent.","author":"Ma"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2021.findings-emnlp.305"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP48485.2024.10445924"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-5421-1_9"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_3"},{"key":"ref34","article-title":"R-GAP: Recursive gradient attack on privacy","author":"Zhu","year":"2021","journal-title":"arXiv:2010.07733"},{"key":"ref35","article-title":"Understanding training-data leakage from gradients in neural networks for image classification","author":"Chen","year":"2021","journal-title":"arXiv:2111.10178"},{"key":"ref36","first-page":"1727","article-title":"Revealing and protecting labels in distributed training","volume-title":"Proc. 35th Adv. Neural Inf. Process. Syst.","author":"Dang"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.2478\/popets-2022-0043"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00919"},{"key":"ref39","first-page":"1","article-title":"QSGD: Communication-efficient SGD via gradient quantization and encoding","volume-title":"Proc. 31st Adv. Neural Inf. Process. Syst.","author":"Alistarh"},{"key":"ref40","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","author":"Lin","year":"2020","journal-title":"arXiv:1712.01887"},{"key":"ref41","article-title":"Variance-based gradient compression for efficient distributed deep learning","author":"Tsuzuku","year":"2018","journal-title":"arXiv:1802.06058"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3378679.3394533"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2988575"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/WACV51458.2022.00366"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3262813"},{"key":"ref46","article-title":"Robbing the fed: Directly obtaining private data in federated learning with modified models","author":"Fowl","year":"2022","journal-title":"arXiv:2110.13057"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP57164.2023.00020"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00387"},{"key":"ref49","volume-title":"Learning Multiple Layers of Features from Tiny Images","author":"Krizhevsky","year":"2009"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3065386"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.425"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref53","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"Radford","year":"2016","journal-title":"arXiv:1511.06434"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1002\/nav.3800020109"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3216981"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ISBI48211.2021.9434062"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/tbdata.2022.3190835"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/s40747-023-00978-9"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/SPW59333.2023.00012"},{"key":"ref60","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-48910-X_16"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6488907\/10643444\/10540055.pdf?arnumber=10540055","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,8,31]],"date-time":"2024-08-31T04:37:59Z","timestamp":1725079079000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10540055\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,1]]},"references-count":60,"journal-issue":{"issue":"17"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3405939","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,1]]}}}