{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T01:30:08Z","timestamp":1774056608253,"version":"3.50.1"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","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\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172441"],"award-info":[{"award-number":["62172441"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62172449"],"award-info":[{"award-number":["62172449"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Joint Funds for Railway Fundamental Research of National Natural Science Foundation of China","award":["U2368201"],"award-info":[{"award-number":["U2368201"]}]},{"name":"National Key Laboratory of Ni&#x0026;Co Associated Minerals Resources Development and Comprehensive Utilization","award":["GZSYS-KY-2022-018"],"award-info":[{"award-number":["GZSYS-KY-2022-018"]}]},{"name":"National Key Laboratory of Ni&#x0026;Co Associated Minerals Resources Development and Comprehensive Utilization","award":["GZSYS-KY-2022-024"],"award-info":[{"award-number":["GZSYS-KY-2022-024"]}]},{"name":"Key Project of Shenzhen City Special Fund for Fundamental Research","award":["JCYJ20220818103200002"],"award-info":[{"award-number":["JCYJ20220818103200002"]}]},{"name":"National Natural Science Foundation of Hunan Province","award":["2023JJ30696"],"award-info":[{"award-number":["2023JJ30696"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Dependable and Secure Comput."],"published-print":{"date-parts":[[2025,1]]},"DOI":"10.1109\/tdsc.2024.3417853","type":"journal-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T18:01:32Z","timestamp":1718992892000},"page":"740-756","source":"Crossref","is-referenced-by-count":9,"title":["A Privacy-Preserving Graph Neural Network for Network Intrusion Detection"],"prefix":"10.1109","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4772-7525","authenticated-orcid":false,"given":"Xinjun","family":"Pei","sequence":"first","affiliation":[{"name":"School of Electronic Information, Shenzhen Research Institute, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2740-8025","authenticated-orcid":false,"given":"Xiaoheng","family":"Deng","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Shenzhen Research Institute, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3525-5102","authenticated-orcid":false,"given":"Shengwei","family":"Tian","sequence":"additional","affiliation":[{"name":"School of Software, Xinjiang University, Wulumuqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3898-4303","authenticated-orcid":false,"given":"Ping","family":"Jiang","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Shenzhen Research Institute, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunlong","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Electronic Information, Shenzhen Research Institute, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2095-7523","authenticated-orcid":false,"given":"Kaiping","family":"Xue","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2910750"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2015.2494502"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICC.2019.8761115"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2023.3344580"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.106795"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978318"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3220076"},{"key":"ref8","first-page":"1","article-title":"Learning differentially private recurrent language models","volume-title":"Proc. Int. Conf. Learn. Representations","author":"McMahan"},{"key":"ref9","first-page":"1","article-title":"How powerful are graph neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Xu"},{"key":"ref10","first-page":"1","article-title":"Semi-supervised classification with graph convolutional networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kipf"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CCWC.2018.8301755"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2799820"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/SSCI47803.2020.9308268"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2019.2897099"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CloudNet51028.2020.9335796"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2660267.2660280"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/TSUSC.2019.2906657"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/WETICE.2019.00073"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/BigData52589.2021.9671428"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.3390\/electronics12163382"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.018.2200349"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00810"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3357384.3357951"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00010"},{"key":"ref25","first-page":"1","article-title":"Graph attention networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Velickovic"},{"key":"ref26","first-page":"1024","article-title":"Inductive representation learning on large graphs","volume-title":"Proc. Int. Conf. Neural Inf. Process. Syst.","author":"Hamilton"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2024.3369017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2024.3454328"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TSC.2023.3241615"},{"key":"ref30","article-title":"FedGNN: Federated graph neural network for privacy-preserving recommendation","author":"Wu","year":"2021"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s00778-022-00768-8"},{"key":"ref32","article-title":"PPSGCN: A privacy-preserving subgraph sampling based distributed GCN training method","author":"Zhang","year":"2021"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611978032.1"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3460120.3484565"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/nana53684.2021.00012"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3198283"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2944748"},{"key":"ref38","volume-title":"Differential Privacy: From Theory to Practice, ser. Synthesis Lectures on Information Security, Privacy, & Trust","author":"Li","year":"2016"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.41"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1148\/radiol.2273011499"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1037\/met0000079"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3442520.3442521"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.5220\/0006105602530262"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/MilCIS.2015.7348942"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2022.3228315"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2939713"},{"key":"ref47","article-title":"Does black-box attribute inference attacks on graph neural networks constitute privacy risk?","author":"Olatunji","year":"2023"},{"key":"ref48","first-page":"6861","article-title":"Simplifying graph convolutional networks","volume-title":"Proc. Proc. Int. Conf. Mach. Learn.","author":"Wu"},{"key":"ref49","article-title":"Topology adaptive graph convolutional networks","author":"Du","year":"2017"}],"container-title":["IEEE Transactions on Dependable and Secure Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/8858\/10843954\/10568382.pdf?arnumber=10568382","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,1,21]],"date-time":"2025-01-21T03:55:54Z","timestamp":1737431754000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10568382\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,1]]},"references-count":49,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tdsc.2024.3417853","relation":{},"ISSN":["1545-5971","1941-0018","2160-9209"],"issn-type":[{"value":"1545-5971","type":"print"},{"value":"1941-0018","type":"electronic"},{"value":"2160-9209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,1]]}}}