{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,5]],"date-time":"2026-11-05T21:16:06Z","timestamp":1793913366776,"version":"4.8.0"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"9","license":[{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,5,1]],"date-time":"2025-05-01T00:00:00Z","timestamp":1746057600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"name":"National Key Research and Development Program of China","award":["2024YFB2906503"],"award-info":[{"award-number":["2024YFB2906503"]}]},{"name":"National Key Research and Development Program of China","award":["2024YFB2906500"],"award-info":[{"award-number":["2024YFB2906500"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62032002"],"award-info":[{"award-number":["62032002"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100013314","name":"Higher Education Discipline Innovation Project","doi-asserted-by":"publisher","award":["B21049"],"award-info":[{"award-number":["B21049"]}],"id":[{"id":"10.13039\/501100013314","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Internet Things J."],"published-print":{"date-parts":[[2025,5,1]]},"DOI":"10.1109\/jiot.2024.3520362","type":"journal-article","created":{"date-parts":[[2024,12,19]],"date-time":"2024-12-19T14:34:22Z","timestamp":1734618862000},"page":"12181-12192","source":"Crossref","is-referenced-by-count":17,"title":["Multivariate Time-Series Anomaly Detection Based on Dynamic Graph Neural Networks and Self-Distillation in Industrial Internet of Things"],"prefix":"10.1109","volume":"12","author":[{"given":"Mengmeng","family":"Zhao","sequence":"first","affiliation":[{"name":"Information Security Center, State Key Laboratory of Networking and Switching Technology, and the National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4415-0126","authenticated-orcid":false,"given":"Haipeng","family":"Peng","sequence":"additional","affiliation":[{"name":"Information Security Center, State Key Laboratory of Networking and Switching Technology, and the National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9949-8731","authenticated-orcid":false,"given":"Lixiang","family":"Li","sequence":"additional","affiliation":[{"name":"Information Security Center, State Key Laboratory of Networking and Switching Technology, and the National Engineering Laboratory for Disaster Backup and Recovery, Beijing University of Posts and Telecommunications, Beijing, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/342009.335388"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/3-540-45681-3_2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1162\/089976601750264965"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/ICCSN.2010.55"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219845"},{"key":"ref6","article-title":"Multivariate industrial time series with cyber-attack simulation: Fault detection using an LSTM-based predictive data model","author":"Filonov","year":"2016","journal-title":"arXiv:1612.06676"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/2689746.2689747"},{"key":"ref8","first-page":"1","article-title":"Deep autoencoding Gaussian mixture model for unsupervised anomaly detection","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Zong"},{"key":"ref9","article-title":"LSTM-based encoder-decoder for multi-sensor anomaly detection","author":"Malhotra","year":"2016","journal-title":"arXiv:1607.00148"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3139916"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011409"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403392"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.14778\/3514061.3514067"},{"key":"ref14","volume-title":"Representation Learning Using a Multi-Branch Transformer for Industrial Time Series Anomaly Detection","author":"Zhang","year":"2022"},{"key":"ref15","article-title":"Anomaly detection with generative adversarial networks for multivariate time series","author":"Li","year":"2018","journal-title":"arXiv:1809.04758"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/616"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-30490-4_56"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3185996"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2801475"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16523"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00093"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2023.3325667"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3100509"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2024.111849"},{"key":"ref25","first-page":"1","article-title":"Interpretable sparse system identification: Beyond recent deep learning techniques on time-series prediction","volume-title":"Proc. 12th Int. Conf. Learn. Represent.","author":"Liu"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33015565"},{"key":"ref27","article-title":"Self-knowledge distillation: A simple way for better generalization","author":"Kim","year":"2020","journal-title":"arXiv:2006.12000"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2019.2958185"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2022.10.008"},{"key":"ref30","first-page":"172","article-title":"A novel anomaly detection scheme based on principal component classifier","volume-title":"Proc. IEEE Found. New Directions Data Min. Workshop","author":"Shyu"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2008.17"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1155\/2009\/837601"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM50108.2020.00147"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.14778\/3467861.3467863"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2886457"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330672"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103094"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.3301922"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539274"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2024.120914"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v34i04.5984"},{"key":"ref42","article-title":"Graph-augmented normalizing flows for anomaly detection of multiple time series","author":"Dai","year":"2022","journal-title":"arXiv:2202.07857"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i4.25623"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1503.02531"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1145\/3097983.3098135"},{"key":"ref46","first-page":"12345","article-title":"Agree to disagree: Adaptive ensemble knowledge distillation in gradient space","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Du"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2023.3288416"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2023.3321505"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2023.102981"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2023.3265964"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2021.3055564"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00381"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1002\/int.22957"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547868"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01576"},{"key":"ref56","article-title":"How powerful are graph neural networks?","author":"Xu","year":"2018","journal-title":"arXiv:1810.00826"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-47578-3"}],"container-title":["IEEE Internet of Things Journal"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6488907\/10975848\/10810265.pdf?arnumber=10810265","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,4,25]],"date-time":"2025-04-25T13:42:06Z","timestamp":1745588526000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10810265\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5,1]]},"references-count":57,"journal-issue":{"issue":"9"},"URL":"https:\/\/doi.org\/10.1109\/jiot.2024.3520362","relation":{},"ISSN":["2327-4662","2372-2541"],"issn-type":[{"value":"2327-4662","type":"electronic"},{"value":"2372-2541","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5,1]]}}}