{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,20]],"date-time":"2026-07-20T10:03:43Z","timestamp":1784541823669,"version":"3.55.0"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,10,1]],"date-time":"2025-10-01T00:00:00Z","timestamp":1759276800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key R&D Program of China","award":["2022YFB2902900"],"award-info":[{"award-number":["2022YFB2902900"]}]},{"DOI":"10.13039\/501100012335","name":"National Defense Basic Scientific Research Program of China","doi-asserted-by":"publisher","award":["JCKY2021602B002"],"award-info":[{"award-number":["JCKY2021602B002"]}],"id":[{"id":"10.13039\/501100012335","id-type":"DOI","asserted-by":"publisher"}]},{"name":"China National Funds for Excellent Young Scientists","award":["62222201"],"award-info":[{"award-number":["62222201"]}]},{"name":"NSFC Projects","award":["U23A20304"],"award-info":[{"award-number":["U23A20304"]}]},{"DOI":"10.13039\/501100005090","name":"Beijing Nova Program","doi-asserted-by":"publisher","award":["20220484174"],"award-info":[{"award-number":["20220484174"]}],"id":[{"id":"10.13039\/501100005090","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["M23020"],"award-info":[{"award-number":["M23020"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["L222098"],"award-info":[{"award-number":["L222098"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004826","name":"Beijing Natural Science Foundation","doi-asserted-by":"publisher","award":["7232041"],"award-info":[{"award-number":["7232041"]}],"id":[{"id":"10.13039\/501100004826","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Big Data"],"published-print":{"date-parts":[[2025,10]]},"DOI":"10.1109\/tbdata.2024.3403388","type":"journal-article","created":{"date-parts":[[2024,5,20]],"date-time":"2024-05-20T13:31:18Z","timestamp":1716211878000},"page":"2135-2147","source":"Crossref","is-referenced-by-count":2,"title":["MemDefense: Defending Against Membership Inference Attacks in IoT-Based Federated Learning via Pruning Perturbations"],"prefix":"10.1109","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1867-0972","authenticated-orcid":false,"given":"Meng","family":"Shen","sequence":"first","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-3387-7911","authenticated-orcid":false,"given":"Jin","family":"Meng","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2587-8517","authenticated-orcid":false,"given":"Ke","family":"Xu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Tsinghua University, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4485-6743","authenticated-orcid":false,"given":"Shui","family":"Yu","sequence":"additional","affiliation":[{"name":"School of Computer Science, University of Technology Sydney, Sydney, NSW, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3277-3887","authenticated-orcid":false,"given":"Liehuang","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Cyberspace Science and Technology, Beijing Institute of Technology, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/IOTM.004.2100182"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/mnet.2023.3327111"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/CSP51677.2021.9357592"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.2980916"},{"key":"ref5","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":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.radonc.2016.10.002"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SPW.2019.00041"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2901840"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3243855"},{"key":"ref11","doi-asserted-by":"crossref","DOI":"10.14722\/ndss.2019.23119","article-title":"ML-leaks: Model and data independent membership inference attacks and defenses on machine learning models","volume-title":"Proc. 26th Annu. Netw. Distrib. Syst. Secur. Symp.","author":"Salem"},{"key":"ref12","article-title":"How to backdoor federated learning","author":"Bagdasaryan","year":"2018"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3028110"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00065"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134077"},{"key":"ref16","article-title":"Understanding membership inferences on well-generalized learning models","author":"Long","year":"2018"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363201"},{"key":"ref18","article-title":"Reconciling utility and membership privacy via knowledge distillation","author":"Shejwalkar","year":"2019"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/2810103.2813687"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2017.2787987"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2929409"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2023.3239007"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3133982"},{"key":"ref24","article-title":"Differentially private federated learning: A client level perspective","author":"Geyer","year":"2017"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2988575"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3378679.3394533"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/432"},{"key":"ref28","first-page":"4561","article-title":"Membership inference attacks and defenses in neural network pruning","volume-title":"Proc. 31st USENIX Secur. Symp.","author":"Yuan"},{"key":"ref29","first-page":"1135","article-title":"Learning both weights and connections for efficient neural network","volume":"28","author":"Han","year":"2015","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref30","first-page":"1387","article-title":"Dynamic network surgery for efficient DNNs","volume":"29","author":"Guo","year":"2016","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3298981"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.03762"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/d17-1045"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CSF.2018.00027"},{"issue":"1","key":"ref35","first-page":"1929","article-title":"Dropout: A simple way to prevent neural networks from overfitting","volume":"15","author":"Srivastava","year":"2014","journal-title":"J. Mach. Learn. Res."},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3127886"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4419-5906-5_752"},{"key":"ref38","first-page":"1895","article-title":"Evaluating differentially private machine learning in practice","volume-title":"Proc. 28th USENIX Secur. Symp.","author":"Jayaraman"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2020.2986619"},{"key":"ref40","article-title":"The lottery ticket hypothesis: Finding sparse, trainable neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Frankle"},{"key":"ref41","first-page":"2579","article-title":"Visualizing data using t-SNE journal of machine learning research","volume":"9","author":"Hinton","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref42","article-title":"Deep gradient compression: Reducing the communication bandwidth for distributed training","volume-title":"Proc. 6th Int. Conf. Learn. Representations","author":"Lin"}],"container-title":["IEEE Transactions on Big Data"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6687317\/11149634\/10535173.pdf?arnumber=10535173","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,5]],"date-time":"2025-09-05T19:16:43Z","timestamp":1757099803000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10535173\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,10]]},"references-count":42,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tbdata.2024.3403388","relation":{},"ISSN":["2332-7790","2372-2096"],"issn-type":[{"value":"2332-7790","type":"electronic"},{"value":"2372-2096","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,10]]}}}