{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,26]],"date-time":"2026-03-26T15:32:57Z","timestamp":1774539177421,"version":"3.50.1"},"reference-count":37,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,3,1]],"date-time":"2023-03-01T00:00:00Z","timestamp":1677628800000},"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":["61873160"],"award-info":[{"award-number":["61873160"]}],"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":["61672338"],"award-info":[{"award-number":["61672338"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100007219","name":"Natural Science Foundation of Shanghai","doi-asserted-by":"publisher","award":["21ZR1426500"],"award-info":[{"award-number":["21ZR1426500"]}],"id":[{"id":"10.13039\/100007219","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Systems Journal"],"published-print":{"date-parts":[[2023,3]]},"DOI":"10.1109\/jsyst.2022.3197447","type":"journal-article","created":{"date-parts":[[2022,8,19]],"date-time":"2022-08-19T19:29:59Z","timestamp":1660937399000},"page":"1158-1169","source":"Crossref","is-referenced-by-count":17,"title":["A Feedback Semi-Supervised Learning With Meta-Gradient for Intrusion Detection"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9910-4499","authenticated-orcid":false,"given":"Shaokang","family":"Cai","sequence":"first","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8861-5461","authenticated-orcid":false,"given":"Dezhi","family":"Han","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1986-7144","authenticated-orcid":false,"given":"Dun","family":"Li","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Shanghai Maritime University, Shanghai, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2019.09.002"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2020.2977646"},{"key":"ref3","first-page":"1","article-title":"Realistic evaluation of deep semi-supervised learning algorithms","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"31","author":"Oliver","year":"2018"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5763"},{"key":"ref5","article-title":"Billion-scale semi-supervised learning for image classification","author":"Yalniz","year":"2019"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00880"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2015.06.004"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSYST.2020.3009447"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2021.04.017"},{"key":"ref10","article-title":"Open-world semi-supervised learning","author":"Cao","year":"2021"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2021.3114621"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3107846"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102587"},{"key":"ref14","article-title":"Semi-supervised learning literature survey","author":"Zhu","year":"2005","journal-title":"Univ. of Wisconsin-Madison"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1504\/IJESDF.2015.070395"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1155\/2021\/5593178"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2917532"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2018.12.002"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/278"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2016.04.007"},{"key":"ref21","article-title":"Temporal ensembling for semi-supervised learning","author":"Laine","year":"2016"},{"key":"ref22","first-page":"1195","article-title":"Mean teachers are better role models: Weight-averaged consistency targets improve semi-supervised deep learning results","volume-title":"Proc. 31st Int. Conf. Neural Inf. Process. Syst.","author":"Tarvainen","year":"2017"},{"key":"ref23","first-page":"6256","article-title":"Unsupervised data augmentation for consistency training","volume":"33","author":"Xie","year":"2020"},{"key":"ref24","first-page":"596","article-title":"FixMatch: Simplifying semi-supervised learning with consistency and confidence","volume":"33","author":"Sohn","year":"2020"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1177\/1550147719846052"},{"key":"ref26","article-title":"An overview of deep semi-supervised learning","author":"Ouali","year":"2020"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/tnn.2009.2015974"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4757-2836-1"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2017.2712906"},{"key":"ref30","first-page":"4334","article-title":"Learning to reweight examples for robust deep learning","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ren","year":"2018"},{"key":"ref31","first-page":"1","article-title":"Meta-weight-net: Learning an explicit mapping for sample weighting","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Shu","year":"2019"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3447548.3467320"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.3182\/20140824-6-za-1003.00295"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.5220\/0006639801080116"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2011.12.012"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1080\/09540091.2021.2024509"}],"container-title":["IEEE Systems Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4267003\/10051137\/09863742.pdf?arnumber=9863742","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,2]],"date-time":"2024-03-02T05:24:18Z","timestamp":1709357058000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9863742\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3]]},"references-count":37,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/jsyst.2022.3197447","relation":{},"ISSN":["1932-8184","1937-9234","2373-7816"],"issn-type":[{"value":"1932-8184","type":"print"},{"value":"1937-9234","type":"electronic"},{"value":"2373-7816","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3]]}}}