{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T22:08:21Z","timestamp":1778882901364,"version":"3.51.4"},"reference-count":33,"publisher":"Elsevier BV","issue":"3","license":[{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2026,3,1]],"date-time":"2026-03-01T00:00:00Z","timestamp":1772323200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:00:00Z","timestamp":1770336000000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003052","name":"Ministry of Trade, Industry and Energy","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100003052","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007053","name":"Korea Institute of Energy Technology Evaluation and Planning","doi-asserted-by":"publisher","award":["RS-2023-00303559"],"award-info":[{"award-number":["RS-2023-00303559"]}],"id":[{"id":"10.13039\/501100007053","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Digital Communications and Networks"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1016\/j.dcan.2026.02.001","type":"journal-article","created":{"date-parts":[[2026,2,18]],"date-time":"2026-02-18T17:01:32Z","timestamp":1771434092000},"page":"451-461","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":0,"title":["Federated anomaly detection in smart grid systems"],"prefix":"10.1016","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1998-4842","authenticated-orcid":false,"given":"Tre\u2019 R.","family":"Jeter","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2861-0439","authenticated-orcid":false,"given":"Raed","family":"Alharbi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0971-8548","authenticated-orcid":false,"given":"Jung Taek","family":"Seo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0503-2012","authenticated-orcid":false,"given":"My T.","family":"Thai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/j.dcan.2026.02.001_bib0001","series-title":"2017 IEEE International Conference on Big Data (Big Data)","first-page":"1975","article-title":"Big data impact on stability and reliability improvement of smart grid","author":"Refaat","year":"2017"},{"issue":"1","key":"10.1016\/j.dcan.2026.02.001_bib0002","doi-asserted-by":"crossref","first-page":"1075","DOI":"10.1109\/TSG.2023.3266809","article-title":"A high-efficiency and incentive-compatible peer-to-peer energy trading mechanism","volume":"15","author":"Guo","year":"2023","journal-title":"IEEE Trans. Smart Grid"},{"issue":"5","key":"10.1016\/j.dcan.2026.02.001_bib0003","doi-asserted-by":"crossref","first-page":"5136","DOI":"10.1109\/TSG.2018.2877999","article-title":"A multilayer and event-triggered voltage and frequency management technique for microgrid\u2019s central controller considering operational and sustainability aspects","volume":"10","author":"Shoeb","year":"2018","journal-title":"IEEE Trans. Smart Grid"},{"key":"10.1016\/j.dcan.2026.02.001_bib0004","doi-asserted-by":"crossref","first-page":"84619","DOI":"10.1109\/ACCESS.2021.3087321","article-title":"An optimal power usage scheduling in smart grid integrated with renewable energy sources for energy management","volume":"9","author":"Rehman","year":"2021","journal-title":"IEEE Access"},{"key":"10.1016\/j.dcan.2026.02.001_bib0005","series-title":"Artificial Intelligence for Sustainability: Innovations in Business and Financial Services","first-page":"153","article-title":"Analysis of smart meter data for energy waste management","author":"Batic","year":"2024"},{"issue":"2","key":"10.1016\/j.dcan.2026.02.001_bib0006","doi-asserted-by":"crossref","first-page":"1273","DOI":"10.1109\/TSG.2021.3128503","article-title":"Monitoring data factorization of high renewable energy penetrated grids for probabilistic static voltage stability assessment","volume":"13","author":"Yang","year":"2021","journal-title":"IEEE Trans. Smart Grid"},{"issue":"3","key":"10.1016\/j.dcan.2026.02.001_bib0007","doi-asserted-by":"crossref","first-page":"4106","DOI":"10.1109\/JSYST.2021.3136683","article-title":"Deep autoencoder-based anomaly detection of electricity theft cyberattacks in smart grids","volume":"16","author":"Takiddin","year":"2022","journal-title":"IEEE Syst. J."},{"issue":"3","key":"10.1016\/j.dcan.2026.02.001_bib0008","doi-asserted-by":"crossref","first-page":"2722","DOI":"10.1109\/TSG.2019.2960459","article-title":"Ultrafast active response strategy against malfunction attack on fault current limiter","volume":"11","author":"Wei","year":"2019","journal-title":"IEEE Trans. Smart Grid"},{"issue":"5","key":"10.1016\/j.dcan.2026.02.001_bib0009","doi-asserted-by":"crossref","first-page":"4881","DOI":"10.1109\/TSG.2018.2870358","article-title":"Coordinated regional-district operation of integrated energy systems for resilience enhancement in natural disasters","volume":"10","author":"Yan","year":"2018","journal-title":"IEEE Trans. Smart Grid"},{"issue":"2","key":"10.1016\/j.dcan.2026.02.001_bib0010","doi-asserted-by":"crossref","first-page":"1113","DOI":"10.1109\/TSG.2021.3128631","article-title":"Flexibility requirement when tracking renewable power fluctuation with peer-to-peer energy sharing","volume":"13","author":"Chen","year":"2021","journal-title":"IEEE Trans. Smart Grid"},{"key":"10.1016\/j.dcan.2026.02.001_bib0011","article-title":"Attention is all you need","volume":"30","author":"Vaswani","year":"2017","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.dcan.2026.02.001_bib0012","series-title":"2014 22nd International Conference on Pattern Recognition","first-page":"3570","article-title":"Statistical anomaly detection in mean and variation of energy consumption","author":"Chen","year":"2014"},{"key":"10.1016\/j.dcan.2026.02.001_bib0013","series-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"353","article-title":"Deep anomaly detection with deviation networks","author":"Pang","year":"2019"},{"key":"10.1016\/j.dcan.2026.02.001_bib0014","series-title":"International Conference on Learning Representations","article-title":"Anomaly transformer: time series anomaly detection with association discrepancy","author":"Xu","year":"2022"},{"key":"10.1016\/j.dcan.2026.02.001_bib0015","first-page":"57947","article-title":"Memto: memory-guided transformer for multivariate time series anomaly detection","volume":"36","author":"Song","year":"2024","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.dcan.2026.02.001_bib0016","series-title":"Kullback-leibler divergence","first-page":"581","author":"Kullback","year":"1951"},{"key":"10.1016\/j.dcan.2026.02.001_bib0017","series-title":"2023 IEEE International Conference on Big Data (BigData)","first-page":"1374","article-title":"Active data reconstruction attacks in vertical federated learning","author":"Vu","year":"2023"},{"key":"10.1016\/j.dcan.2026.02.001_bib0018","article-title":"Generative adversarial nets","volume":"27","author":"Goodfellow","year":"2014","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.dcan.2026.02.001_bib0019","series-title":"Conditional Generative Adversarial Nets","author":"Mirza","year":"2014"},{"key":"10.1016\/j.dcan.2026.02.001_bib0020","series-title":"International Conference on Learning Representations","article-title":"Robust conditional generative adversarial networks","author":"Chrysos","year":"2018"},{"key":"10.1016\/j.dcan.2026.02.001_bib0021","first-page":"13016","article-title":"Timeseries anomaly detection using temporal hierarchical one-class network","volume":"33","author":"Shen","year":"2020","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"10.1016\/j.dcan.2026.02.001_bib0022","series-title":"Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining","first-page":"3220","article-title":"Multivariate time series anomaly detection and interpretation using hierarchical inter-metric and temporal embedding","author":"Li","year":"2021"},{"key":"10.1016\/j.dcan.2026.02.001_bib0023","series-title":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","first-page":"2828","article-title":"Robust anomaly detection for multivariate time series through stochastic recurrent neural network","author":"Su","year":"2019"},{"key":"10.1016\/j.dcan.2026.02.001_bib0024","series-title":"7th International Conference on Learning Representations, ICLR 2019, New Orleans, LA, USA, May 6\u20139, 2019","article-title":"Music transformer: generating music with long-term structure","author":"Huang","year":"2019"},{"key":"10.1016\/j.dcan.2026.02.001_bib0025","series-title":"The Eleventh International Conference on Learning Representations","article-title":"TimesNet: temporal 2D-variation modeling for general time series analysis","author":"Wu","year":"2022"},{"issue":"6","key":"10.1016\/j.dcan.2026.02.001_bib0026","doi-asserted-by":"crossref","first-page":"1201","DOI":"10.14778\/3514061.3514067","article-title":"TranAD: deep transformer networks for anomaly detection in multivariate time series data","volume":"15","author":"Tuli","year":"2022","journal-title":"Proc. VLDB Endow."},{"issue":"5","key":"10.1016\/j.dcan.2026.02.001_bib0027","doi-asserted-by":"crossref","first-page":"2505","DOI":"10.1109\/TSG.2017.2703842","article-title":"Real-time detection of false data injection attacks in smart grid: a deep learning-based intelligent mechanism","volume":"8","author":"He","year":"2017","journal-title":"IEEE Trans. Smart Grid"},{"issue":"6","key":"10.1016\/j.dcan.2026.02.001_bib0028","doi-asserted-by":"crossref","first-page":"4862","DOI":"10.1109\/TSG.2022.3204796","article-title":"Detection of false data injection attacks in smart grid: a secure federated deep learning approach","volume":"13","author":"Li","year":"2022","journal-title":"IEEE Trans. Smart Grid"},{"issue":"2","key":"10.1016\/j.dcan.2026.02.001_bib0029","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3588439","article-title":"A robust learning framework for smart grids in defense against false-data injection attacks","volume":"20","author":"Miao","year":"2024","journal-title":"ACM Trans. Sens. Netw."},{"key":"10.1016\/j.dcan.2026.02.001_bib0030","series-title":"2022 IEEE International Conference on Big Data (Big Data)","first-page":"1090","article-title":"Decomposed transformer with frequency attention for multivariate time series anomaly detection","author":"Qin","year":"2022"},{"key":"10.1016\/j.dcan.2026.02.001_bib0031","series-title":"2018 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)","first-page":"1","article-title":"Generative adversarial network for synthetic time series data generation in smart grids","author":"Zhang","year":"2018"},{"issue":"5","key":"10.1016\/j.dcan.2026.02.001_bib0032","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3643822","article-title":"Networked time series prediction with incomplete data via generative adversarial network","volume":"18","author":"Zhu","year":"2024","journal-title":"ACM Trans. Knowl. Discovery Data"},{"issue":"4","key":"10.1016\/j.dcan.2026.02.001_bib0033","doi-asserted-by":"crossref","first-page":"3203","DOI":"10.1109\/TSG.2022.3159842","article-title":"A GAN-based data injection attack method on data-driven strategies in power systems","volume":"13","author":"Liu","year":"2022","journal-title":"IEEE Trans. Smart Grid"}],"container-title":["Digital Communications and Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352864826000027?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S2352864826000027?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2026,5,15]],"date-time":"2026-05-15T21:18:46Z","timestamp":1778879926000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S2352864826000027"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,3]]},"references-count":33,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["S2352864826000027"],"URL":"https:\/\/doi.org\/10.1016\/j.dcan.2026.02.001","relation":{},"ISSN":["2352-8648"],"issn-type":[{"value":"2352-8648","type":"print"}],"subject":[],"published":{"date-parts":[[2026,3]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Federated anomaly detection in smart grid systems","name":"articletitle","label":"Article Title"},{"value":"Digital Communications and Networks","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.dcan.2026.02.001","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2026 Chongqing University of Posts and Telecommunications. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co. Ltd. All rights are reserved, including those for text and data mining, AI training, and similar technologies.","name":"copyright","label":"Copyright"}]}}