{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,11]],"date-time":"2026-04-11T01:31:36Z","timestamp":1775871096683,"version":"3.50.1"},"reference-count":21,"publisher":"IEEE","license":[{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,5,28]],"date-time":"2023-05-28T00:00:00Z","timestamp":1685232000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,5,28]]},"DOI":"10.1109\/icc45041.2023.10279032","type":"proceedings-article","created":{"date-parts":[[2023,10,23]],"date-time":"2023-10-23T13:54:10Z","timestamp":1698069250000},"page":"2988-2993","source":"Crossref","is-referenced-by-count":11,"title":["SF-IDS: An Imbalanced Semi-Supervised Learning Framework for Fine-Grained Intrusion Detection"],"prefix":"10.1109","author":[{"given":"Xinran","family":"Zheng","sequence":"first","affiliation":[{"name":"Tsinghua Shenzhen International Graduate School, Tsinghua University,Shenzhen,China"}]},{"given":"Shuo","family":"Yang","sequence":"additional","affiliation":[{"name":"Tsinghua Shenzhen International Graduate School, Tsinghua University,Shenzhen,China"}]},{"given":"Xingjun","family":"Wang","sequence":"additional","affiliation":[{"name":"Tsinghua Shenzhen International Graduate School, Tsinghua University,Shenzhen,China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2933165"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2020.107315"},{"key":"ref15","article-title":"Semi-wtc: A practical semi-supervised framework for attack categorization through weight-task consistency","author":"li","year":"2022","journal-title":"ArXiv Preprint"},{"key":"ref14","first-page":"3833","article-title":"Rethinking pre-training and self-training","volume":"33","author":"zoph","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref20","first-page":"18661","article-title":"Supervised contrastive learning","volume":"33","author":"khosla","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2022.107720"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.115524"},{"key":"ref21","first-page":"596","article-title":"Fixmatch: Simplifying semi-supervised learning with consistency and confidence","volume":"33","author":"sohn","year":"2020","journal-title":"Advances in neural information processing systems"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2022.3195534"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2873125"},{"key":"ref17","first-page":"1050","article-title":"Dropout as a bayesian approximation: Representing model uncertainty in deep learning","volume":"48","author":"gal","year":"0","journal-title":"Proceedings of the 33rd International Conference on International Conference on Machine Learning"},{"key":"ref16","article-title":"In defense of pseudo-labeling: An uncertainty-aware pseudo-label selection framework for semi-supervised learning","author":"rizve","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.580"},{"key":"ref18","first-page":"878","article-title":"Borderline-smote: a new over-sampling method in imbalanced data sets learning","author":"han","year":"0","journal-title":"International Conference on Intelligent Computing"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-10-4642-1_5"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/1229285.1229292"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2020.3025755"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1145\/3178582"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2021.3120804"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1016\/j.dss.2004.06.016"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2017.09.014"}],"event":{"name":"ICC 2023 - IEEE International Conference on Communications","location":"Rome, Italy","start":{"date-parts":[[2023,5,28]]},"end":{"date-parts":[[2023,6,1]]}},"container-title":["ICC 2023 - IEEE International Conference on Communications"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10278505\/10278554\/10279032.pdf?arnumber=10279032","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T14:00:35Z","timestamp":1699884035000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10279032\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,5,28]]},"references-count":21,"URL":"https:\/\/doi.org\/10.1109\/icc45041.2023.10279032","relation":{},"subject":[],"published":{"date-parts":[[2023,5,28]]}}}