{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T03:43:37Z","timestamp":1782445417668,"version":"3.54.5"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2022YFE0114200"],"award-info":[{"award-number":["2022YFE0114200"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62471121"],"award-info":[{"award-number":["62471121"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["N2424010-18"],"award-info":[{"award-number":["N2424010-18"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shenyang Science and Technology Plan Fund Project","award":["23-503-6-17"],"award-info":[{"award-number":["23-503-6-17"]}]},{"name":"Liaoning Provincial Science and Technology Plan Project","award":["2023JH2\/101700370"],"award-info":[{"award-number":["2023JH2\/101700370"]}]},{"DOI":"10.13039\/501100014206","name":"Fund of National Key Laboratory of Metallurgical Intelligent Manufacturing System","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100014206","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tifs.2025.3588324","type":"journal-article","created":{"date-parts":[[2025,7,11]],"date-time":"2025-07-11T17:43:17Z","timestamp":1752255797000},"page":"7617-7632","source":"Crossref","is-referenced-by-count":5,"title":["PDSA-FL: A Poisoning-Defense Secure Aggregation in Federated Learning"],"prefix":"10.1109","volume":"20","author":[{"ORCID":"https:\/\/orcid.org\/0009-0006-2244-435X","authenticated-orcid":false,"given":"Zixuan","family":"Huang","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8424-8542","authenticated-orcid":false,"given":"Yuanguo","family":"Bi","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4262-153X","authenticated-orcid":false,"given":"Kuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5488-9728","authenticated-orcid":false,"given":"Bing","family":"Hu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6518-3130","authenticated-orcid":false,"given":"Zhou","family":"Su","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Xi&#x2019;an Jiaotong University, Xi&#x2019;an, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-0901-9890","authenticated-orcid":false,"given":"Chong","family":"Tai","sequence":"additional","affiliation":[{"name":"Neusoft Corporation, Shenyang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-9327-9706","authenticated-orcid":false,"given":"Xukun","family":"Luan","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Northeastern University, Shenyang, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"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.","volume":"54","author":"McMahan"},{"key":"ref2","article-title":"Federated learning: Strategies for improving communication efficiency","author":"Kone\u010d n\u00fd","year":"2016","journal-title":"arXiv:1610.05492"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/s41666-020-00082-4"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2021.3081560"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3383455.3422562"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2023.3322841"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3460427"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813677"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/infocom.2019.8737416"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/tdsc.2021.3128679"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/3543507.3583359"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2023.3346692"},{"key":"ref13","first-page":"1397","article-title":"Label inference attacks against vertical federated learning","volume-title":"Proc. 31st USENIX Security Symp. (USENIX Security)","author":"Fu"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/PAAP60200.2023.10391773"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2024.04.024"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref17","first-page":"1605","article-title":"Local model poisoning attacks to Byzantine-robust federated learning","volume-title":"Proc. 29th USENIX Secur. Symp.","author":"Fang"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/trustcom53373.2021.00062"},{"key":"ref19","first-page":"2938","article-title":"How to backdoor federated learning","volume-title":"Proc. Int. Conf. Artif. Intell. Statist.","author":"Bagdasaryan"},{"key":"ref20","first-page":"1","article-title":"DBA: Distributed backdoor attacks against federated learning","volume-title":"Proc. ICLR","author":"Xie"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2024.3437482"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2021.3108434"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2023.3280032"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2024.3376255"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3372297.3417885"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/jsait.2021.3054610"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/isit50566.2022.9834750"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/jsac.2023.3242702"},{"key":"ref29","first-page":"694","article-title":"LightSecAgg: A lightweight and versatile design for secure aggregation in federated learning","volume":"4","author":"So","year":"2021","journal-title":"Proc. Mach. Learn. Syst."},{"key":"ref30","article-title":"FastSecAgg: Scalable secure aggregation for privacy-preserving federated learning","author":"Kadhe","year":"2020","journal-title":"arXiv:2009.11248"},{"key":"ref31","first-page":"118","article-title":"Machine learning with adversaries: Byzantine tolerant gradient descent","volume-title":"Proc. NeurIPS","volume":"30","author":"Blanchard"},{"key":"ref32","first-page":"5650","article-title":"Byzantine-robust distributed learning: Towards optimal statistical rates","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Yin"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24434"},{"key":"ref34","first-page":"1641","article-title":"Justinian\u2019s GAAvernor: Robust distributed learning with gradient aggregation agent","volume-title":"Proc. USENIX Secur.","author":"Pan"},{"key":"ref35","article-title":"Mitigating Sybils in federated learning poisoning","author":"Fung","year":"2018","journal-title":"arXiv:1808.04866"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/tsp.2020.3012952"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/106"},{"key":"ref38","article-title":"Mitigating Sybil attacks on differential privacy based federated learning","author":"Jiang","year":"2020","journal-title":"arXiv:2010.10572"},{"key":"ref39","first-page":"1","article-title":"A little is enough: Circumventing defenses for distributed learning","volume-title":"Proc. NeurIPS","volume":"32","author":"Baruch"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2021.24498"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2023.3249568"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/TIT.1976.1055638"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/10810755\/11078290.pdf?arnumber=11078290","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,26]],"date-time":"2025-07-26T06:30:59Z","timestamp":1753511459000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11078290\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/tifs.2025.3588324","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}