{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T16:20:39Z","timestamp":1774369239554,"version":"3.50.1"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","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:\/\/creativecommons.org\/licenses\/by\/4.0\/legalcode"}],"funder":[{"DOI":"10.13039\/501100011089","name":"Infrastruktura PL-Grid","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100011089","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Polish Ministry of Science and Higher Education allocated to the AGH University"},{"name":"Program \u201cExcellence Initiative\u2014Research University\u201d for AGH University"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Neural Netw. Learning Syst."],"published-print":{"date-parts":[[2025,5]]},"DOI":"10.1109\/tnnls.2024.3439404","type":"journal-article","created":{"date-parts":[[2024,8,14]],"date-time":"2024-08-14T17:39:12Z","timestamp":1723657152000},"page":"8939-8953","source":"Crossref","is-referenced-by-count":4,"title":["AD-NEv: A Scalable Multilevel Neuroevolution Framework for Multivariate Anomaly Detection"],"prefix":"10.1109","volume":"36","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9357-9231","authenticated-orcid":false,"given":"Marcin","family":"Pietro\u0144","sequence":"first","affiliation":[{"name":"Faculty of Computer Science, AGH University of Krakow, Krak&#x00F3;w, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5329-1452","authenticated-orcid":false,"given":"Dominik","family":"\u017burek","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, AGH University of Krakow, Krak&#x00F3;w, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4221-0017","authenticated-orcid":false,"given":"Kamil","family":"Faber","sequence":"additional","affiliation":[{"name":"Faculty of Computer Science, AGH University of Krakow, Krak&#x00F3;w, Poland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8366-6059","authenticated-orcid":false,"given":"Roberto","family":"Corizzo","sequence":"additional","affiliation":[{"name":"Department of Computer Science, American University, Washington, DC, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3439950"},{"key":"ref2","first-page":"1","article-title":"LSTM-based encoder\u2013decoder for multi-sensor anomaly detection","author":"Malhotra","year":"2016","journal-title":"CoRR"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2019\/616"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/TII.2019.2945366"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330672"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3394486.3403392"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3292500.3330776"},{"key":"ref8","first-page":"1","article-title":"Deep learning for unsupervised insider threat detection in structured cybersecurity data streams","volume-title":"Proc. Workshops 31st AAAI Conf. Artif. Intell.","author":"Tuor"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011286"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1186\/s42400-022-00134-9"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2023.05.032"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-88942-5_36"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/JHEP06(2021)161"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3107163"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/LRA.2018.2801475"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3337243"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i5.16523"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3325667"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2024.3371109"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3219819.3219845"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3105827"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2023.3337876"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1162\/106365602320169811"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1162\/artl.2009.15.2.15202"},{"key":"ref25","first-page":"1","article-title":"Evolving deep neural networks","author":"Miikkulainen","year":"2017","journal-title":"CoRR"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.3390\/e23111466"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/1541880.1541882"},{"key":"ref28","article-title":"Deep learning for anomaly detection: A survey","author":"Chalapathy","year":"2019","journal-title":"arXiv:1901.03407"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3107975"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.mlwa.2023.100470"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3464423"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3444690"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.03.062"},{"key":"ref34","article-title":"An empirical evaluation of generic convolutional and recurrent networks for sequence modeling","author":"Bai","year":"2018","journal-title":"arXiv:1803.01271"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011409"},{"key":"ref36","first-page":"1","article-title":"Deep autoencoding Gaussian mixture model for unsupervised anomaly detection","volume-title":"Proc. ICLR","author":"Zong"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/TAI.2021.3067574"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2016.2551748"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2854833"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2022.3187741"},{"key":"ref41","first-page":"1","article-title":"MONCAE: Multi-objective neuroevolution of convolutional autoencoders","volume-title":"Proc. ICLR","author":"Dimanov"},{"issue":"6","key":"ref42","first-page":"127","article-title":"Neuroevolution of autoencoders by genetic algorithm","volume":"6","author":"Okada","year":"2017","journal-title":"Int. J. Sci. Eng. Invest."},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3094987"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2021.3059669"},{"key":"ref45","first-page":"7197","article-title":"Up or down? Adaptive rounding for post-training quantization","volume-title":"Proc. ICML","author":"Nagel"},{"key":"ref46","first-page":"1","article-title":"Adversarial autoencoders","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Makhzani"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1145\/3178876.3185996"},{"key":"ref48","first-page":"1","article-title":"Generalized denoising auto-encoders as generative models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"26","author":"Bengio"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1007\/s00453-012-9717-4"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/CySWater.2016.7469060"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1145\/3055366.3055375"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i7.20680"}],"container-title":["IEEE Transactions on Neural Networks and Learning Systems"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/5962385\/10982361\/10636086.pdf?arnumber=10636086","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,5]],"date-time":"2025-05-05T17:58:11Z","timestamp":1746467891000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10636086\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,5]]},"references-count":52,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tnnls.2024.3439404","relation":{},"ISSN":["2162-237X","2162-2388"],"issn-type":[{"value":"2162-237X","type":"print"},{"value":"2162-2388","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,5]]}}}