{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T06:38:50Z","timestamp":1776926330692,"version":"3.51.2"},"reference-count":32,"publisher":"Tech Science Press","issue":"3","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":214,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.064696","type":"journal-article","created":{"date-parts":[[2025,6,5]],"date-time":"2025-06-05T03:49:31Z","timestamp":1749095371000},"page":"4431-4449","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":1,"title":["SA-WGAN Based Data Enhancement Method for Industrial Internet Intrusion Detection"],"prefix":"10.32604","volume":"84","author":[{"given":"Yuan","family":"Feng","sequence":"first","affiliation":[]},{"given":"Yajie","family":"Si","sequence":"additional","affiliation":[]},{"given":"Jianwei","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Zengyu","family":"Cai","sequence":"additional","affiliation":[]},{"given":"Hongying","family":"Zhao","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","doi-asserted-by":"crossref","first-page":"107485","DOI":"10.1016\/j.ress.2021.107485","article-title":"Analysis of cybersecurity-related incidents in the process industry","volume":"209","author":"Iaiani","year":"2021","journal-title":"Reliab Eng Syst Saf"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"7154587","DOI":"10.1155\/2021\/7154587","article-title":"Intrusion detection in industrial internet of things network-based on deep learning model with rule-based feature selection","volume":"2021","author":"Awotunde","year":"2021","journal-title":"Wirel Commun Mob Comput"},{"key":"ref3","doi-asserted-by":"crossref","first-page":"371","DOI":"10.1016\/j.aej.2023.09.023","article-title":"Deep learning-based intrusion detection approach for securing industrial Internet of Things","volume":"81","author":"Soliman","year":"2023","journal-title":"Alex Eng J"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"1567","DOI":"10.32604\/csse.2023.025216","article-title":"Intelligent intrusion detection system for industrial internet of things environment","volume":"44","author":"Gopi","year":"2023","journal-title":"Comput Syst Sci Eng"},{"key":"ref5","doi-asserted-by":"crossref","first-page":"9023719","DOI":"10.1155\/2022\/9023719","article-title":"Intrusion detection system for industrial Internet of Things based on deep reinforcement learning","volume":"2022","author":"Tharewal","year":"2022","journal-title":"Wirel Commun Mob Comput"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"3939895","DOI":"10.1155\/2023\/3939895","article-title":"Industrial internet of things intrusion detection method using machine learning and optimization techniques","volume":"2023","author":"Gaber","year":"2023","journal-title":"Wirel Commun Mob Comput"},{"key":"ref7","first-page":"321","article-title":"SMOTE: synthetic minority over-sampling technique","volume":"16","author":"Nitesh","year":"2022","journal-title":"J Artif Intell Res"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"105845","DOI":"10.1016\/j.knosys.2020.105845","article-title":"LR-SMOTE\u2014improved unbalanced data set oversampling based on K-means and SVM. 2002","volume":"196","author":"Liang","year":"2020","journal-title":"Knowl-Based Syst"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"9793","DOI":"10.1007\/s00521-022-06965-4","article-title":"DEIDS: a novel intrusion detection system for industrial control systems","volume":"34","author":"Gu","year":"2022","journal-title":"Neural Comput Appl"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.ins.2018.06.056","article-title":"Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE","volume":"465","author":"Douzas","year":"2018","journal-title":"Inf Sci"},{"key":"ref11","author":"Nwe","year":"2020","journal-title":"Software engineering research, management and applications"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.ins.2019.08.062","article-title":"Neighbourhood-based undersampling approach for handling imbalanced and overlapped data","volume":"509","author":"Vuttipittayamongkol","year":"2020","journal-title":"Inf Sci"},{"key":"ref13","first-page":"6376","article-title":"Spatial distribution-based imbalanced undersampling","volume":"35","author":"Yan","year":"2022","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"2697303","DOI":"10.1155\/2022\/2697303","article-title":"A machine learning-based model for stability prediction of decentralized power grid linked with renewable energy resources","volume":"2022","author":"Ibrar","year":"2022","journal-title":"Wirel Commun Mob Comput"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"47","DOI":"10.1016\/j.ins.2018.10.029","article-title":"Under-sampling class imbalanced datasets by combining clustering analysis and instance selection","volume":"477","author":"Tsai","year":"2019","journal-title":"Inf Sci"},{"key":"ref16","doi-asserted-by":"crossref","first-page":"119030","DOI":"10.1016\/j.eswa.2022.119030","article-title":"Dual-IDS: a bagging-based gradient boosting decision tree model for network anomaly intrusion detection system","volume":"213","author":"Louk","year":"2023","journal-title":"Expert Syst Appl"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"4","DOI":"10.3390\/sym13010004","article-title":"Effectiveness of focal loss for minority classification in network intrusion detection systems","volume":"13","author":"Mulyanto","year":"2020","journal-title":"Symmetry"},{"key":"ref18","doi-asserted-by":"crossref","first-page":"102499","DOI":"10.1016\/j.cose.2021.102499","article-title":"CSE-IDS: using cost-sensitive deep learning and ensemble algorithms to handle class imbalance in network-based intrusion detection systems","volume":"112","author":"Gupta","year":"2022","journal-title":"Comput Secur"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"780","DOI":"10.1016\/j.procs.2020.04.085","article-title":"Siam-IDS: handling class imbalance problem in intrusion detection systems using siamese neural network","volume":"171","author":"Bedi","year":"2020","journal-title":"Procedia Comput Sci"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"1133","DOI":"10.1007\/s10489-020-01886-y","article-title":"I-SiamIDS: an improved Siam-IDS for handling class imbalance in network-based intrusion detection systems","volume":"51","author":"Bedi","year":"2021","journal-title":"Appl Intell"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1080\/0952813X.2022.2104384","article-title":"Intrusion detection method based on imbalanced learning classification","volume":"36","author":"Li","year":"2024","journal-title":"J Exp Theor Artif Intell"},{"key":"ref22","doi-asserted-by":"crossref","first-page":"107378","DOI":"10.1016\/j.asoc.2021.107378","article-title":"Online ensemble learning algorithm for imbalanced data stream","volume":"107","author":"Du","year":"2021","journal-title":"Appl Soft Comput"},{"key":"ref23","doi-asserted-by":"crossref","first-page":"1461","DOI":"10.3390\/sym14071461","article-title":"Advanced feature-selection-based hybrid ensemble learning algorithms for network intrusion detection systems","volume":"14","author":"Mhawi","year":"2022","journal-title":"Symmetry"},{"key":"ref24","series-title":"Proceedings of the 2020 IEEE 44th Annual Computers, Software, and Applications Conference (COMPSAC)","article-title":"G-IDS: generative adversarial networks assisted intrusion detection system","author":"Shahriar","year":"2020 Jul 13\u201317"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"1156","DOI":"10.1109\/TIFS.2023.3331240","article-title":"TMG-GAN: generative adversarial networks-based imbalanced learning for network intrusion detection","volume":"19","author":"Ding","year":"2023","journal-title":"IEEE Trans Inf Forensics Secur"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/s00779-019-01332-y","article-title":"GAN-based imbalanced data intrusion detection system","volume":"25","author":"Lee","year":"2021","journal-title":"Pers Ubiquit Comput"},{"key":"ref27","series-title":"Proceedings of the 33rd Chinese Control and Decision Conference (CCDC)","article-title":"GAN-based intrusion detection data enhancement","author":"Fu","year":"2021 May 22\u201324"},{"key":"ref28","first-page":"507","article-title":"A method for network intrusion detection based on GAN-CNN-BiLSTM","volume":"14","author":"Li","year":"2023","journal-title":"Int J Adv Comput Sci Appl"},{"key":"ref29","unstructured":"Goodfellow I, Pouget-Abadie J, Mirza M, Xu B, Warde-Farley D, Ozair S. Generative adversarial nets. Advances in neural information processing systems. arXiv:1406.2661. 2014."},{"key":"ref30","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/S0016-0032(96)00063-4","article-title":"The Jensen-Shannon divergence","volume":"334","author":"Men\u00e9ndez","year":"1997","journal-title":"J Frankl Inst"},{"key":"ref31","series-title":"Proceedings of the International Conference on Machine Learning","article-title":"Wasserstein generative adversarial networks","author":"Arjovsky","year":"2017 Aug 6\u201311"},{"key":"ref32","volume":"441","author":"Morris","year":"2014","journal-title":"Critical infrastructure protection VIII"}],"container-title":["Computers, Materials & Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-84-3\/TSP_CMC_64696\/TSP_CMC_64696.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T05:45:22Z","timestamp":1776923122000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v84n3\/63141"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":32,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.064696","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2025-02-21","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-05-14","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-30","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}