{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,9]],"date-time":"2026-04-09T14:48:28Z","timestamp":1775746108691,"version":"3.50.1"},"reference-count":38,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,12,1]],"date-time":"2024-12-01T00:00:00Z","timestamp":1733011200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"Key Research and Development Program of Zhejiang Province of China","award":["2020C01024"],"award-info":[{"award-number":["2020C01024"]}]},{"DOI":"10.13039\/501100001381","name":"National Research Foundation Singapore","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"AI Singapore Programme","award":["AISG2-RP-2020-019"],"award-info":[{"award-number":["AISG2-RP-2020-019"]}]},{"name":"Joint NTU-WeBank Research Centre on Fintech","award":["NWJ-2020-008"],"award-info":[{"award-number":["NWJ-2020-008"]}]},{"name":"Nanyang Assistant Professorships"},{"name":"RIE 2020 Advanced Manufacturing and Engineering Programmatic Fund","award":["A20G8b0102"],"award-info":[{"award-number":["A20G8b0102"]}]},{"name":"SDU-NTU Centre for AI Research"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2024,12]]},"DOI":"10.1109\/tbdata.2022.3159236","type":"journal-article","created":{"date-parts":[[2022,3,15]],"date-time":"2022-03-15T19:43:16Z","timestamp":1647373396000},"page":"851-863","source":"Crossref","is-referenced-by-count":19,"title":["Practical Attribute Reconstruction Attack Against Federated Learning"],"prefix":"10.1109","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-7359-8515","authenticated-orcid":false,"given":"Chen","family":"Chen","sequence":"first","affiliation":[{"name":"College of Computer Science and Technology, Zhejiang University, Hangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3170-4994","authenticated-orcid":false,"given":"Lingjuan","family":"Lyu","sequence":"additional","affiliation":[{"name":"Sony AI, Tokyo, Japan"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6893-8650","authenticated-orcid":false,"given":"Han","family":"Yu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7483-0045","authenticated-orcid":false,"given":"Gang","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of CAD&CG, College of Computer Science and Technology, Zhejiang University, Hangzhou, 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. 20th Int. Conf. Artif. Intell. Statist.","author":"McMahan"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2940820"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3011726"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.011.2000195"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_1"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3216981"},{"key":"ref7","article-title":"Robust federated recommendation system","author":"Chen","year":"2020"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00029"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134012"},{"key":"ref10","first-page":"14 747","article-title":"Deep leakage from gradients","volume-title":"Proc. 33rd Int. Conf. Neural Inf. Process. Syst.","author":"Zhu"},{"key":"ref11","article-title":"iDLG: Improved deep leakage from gradients","author":"Zhao","year":"2020"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.5555\/2969033.2969125"},{"key":"ref13","first-page":"17","article-title":"Privacy in pharmacogenetics: An end-to-end case study of personalized warfarin dosing","volume-title":"Proc. 23rd USENIX Secur. Symp.","author":"Fredrikson"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2018.00027"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/cvpr42600.2020.00033"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00408"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2021.3128560"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2005"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D18-1001"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1145\/2736277.2741141"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2020.findings-emnlp.213"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3446776"},{"key":"ref25","article-title":"Overlearning reveals sensitive attributes","author":"Song","year":"2019"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417270"},{"key":"ref27","article-title":"Dataset-level attribute leakage in collaborative learning","author":"Zhang","year":"2020"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.29012\/jpc.v2i1.585"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1561\/9781601988195"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2020.3006287"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/216"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/2020408.2020598"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16960"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00095"},{"key":"ref38","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","author":"Lin","year":"2017"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6687317\/10750532\/09735364.pdf?arnumber=9735364","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,27]],"date-time":"2024-11-27T15:23:18Z","timestamp":1732720998000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9735364\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12]]},"references-count":38,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2022.3159236","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"value":"2332-7790","type":"electronic"},{"value":"2372-2096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12]]}}}