{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T20:38:13Z","timestamp":1776890293933,"version":"3.51.2"},"reference-count":52,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,1,1]],"date-time":"2026-01-01T00:00:00Z","timestamp":1767225600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62402330"],"award-info":[{"award-number":["62402330"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62366052"],"award-info":[{"award-number":["62366052"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"the Sichuan Provincial Science and Technology Department regional innovation cooperation key project","award":["2025YFHZ0265"],"award-info":[{"award-number":["2025YFHZ0265"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2026]]},"DOI":"10.1109\/tifs.2026.3673137","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T19:36:32Z","timestamp":1773257792000},"page":"3137-3152","source":"Crossref","is-referenced-by-count":0,"title":["Exploratory Detection of Unknown Cyber-Attacks via Evolutionary Strategy and Machine Learning"],"prefix":"10.1109","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2100-4794","authenticated-orcid":false,"given":"Wenbo","family":"Fang","sequence":"first","affiliation":[{"name":"College of Science and Artificial Intelligence, Southwest Minzu University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0002-6143-9677","authenticated-orcid":false,"given":"Gang","family":"Li","sequence":"additional","affiliation":[{"name":"School of Software, Chengdu University of Information Technology, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sunjun","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Software, Chengdu University of Information Technology, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-6445-3450","authenticated-orcid":false,"given":"Linlin","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Software, Xinjiang University, Ürümqi, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Menghao","family":"Ao","sequence":"additional","affiliation":[{"name":"School of Software, Chengdu University of Information Technology, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qikai","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software, Chengdu University of Information Technology, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7040-2425","authenticated-orcid":false,"given":"Junjiang","family":"He","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","volume-title":"Kaspersky Security Bulletin 2024. Statistics","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1002\/9781394166954.ch2"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ICDIS50059.2020.00016"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM41043.2020.9155278"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/THS.2017.7943467"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/ICMLA.2017.000-3"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.06.104"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1002\/ett.4212"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2020.2991876"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.23919\/CNSM59352.2023.10327888"},{"key":"ref11","first-page":"807","article-title":"Optimized invariant representation of network traffic for detecting unseen malware variants","volume-title":"Proc. 25th USENIX Secur. Symp.","author":"Bartos"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2024.3365101"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/s10586-024-04840-6"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2025.3528256"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2025.3545363"},{"key":"ref16","first-page":"147","article-title":"Immunity-based intrusion detection system: A general framework","volume-title":"Proc. 22nd NISSC","author":"Dasgupta"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103675"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.3390\/sym12111931"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3520304.3533999"},{"key":"ref20","volume-title":"IBM X-Force Threat Intelligence Index 2024\u2013Executive Summary","year":"2025"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1145\/3449639.3459351"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2024.3413789"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3083422"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2025.3594569"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2766844"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.artint.2023.104059"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2024.3385745"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2021.3105614"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2023.3325001"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TGRS.2023.3309091"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1080\/00396338.2011.555586"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.5555\/3241189.3241275"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.58679\/mm28378"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.3390\/s21217070"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/4175.001.0001"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.05.027"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-36657-4_7"},{"issue":"2","key":"ref38","first-page":"896","article-title":"Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks","volume-title":"Proc. Workshop challenges Represent. Learn.","volume":"3","author":"Lee"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i5.28269"},{"key":"ref40","article-title":"A unified survey on anomaly, novelty, open-set, and out-of-distribution detection: Solutions and future challenges","author":"Salehi","year":"2021","journal-title":"arXiv:2110.14051"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2014.06.011"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v31i1.10894"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1995.7.2.219"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1007\/s11063-018-9903-8"},{"key":"ref45","first-page":"1033","article-title":"The concave-convex procedure (CCCP)","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"14","author":"Yuille"},{"key":"ref46","article-title":"Why gradient clipping accelerates training: A theoretical justification for adaptivity","author":"Zhang","year":"2019","journal-title":"arXiv:1905.11881"},{"issue":"36","key":"ref47","first-page":"725","article-title":"Karush-kuhn-tucker conditions","volume":"10","author":"Gordon","year":"2012","journal-title":"Optimization"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2023.3318638"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/MilCIS.2015.7348942"},{"key":"ref50","volume-title":"Canadian Institute for Cybersecurity","year":"2020"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref52","volume-title":"CSE-CIC-IDS2018 Dataset","author":"Sharafaldin","year":"2025"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/11313711\/11430692.pdf?arnumber=11430692","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,22]],"date-time":"2026-04-22T19:48:30Z","timestamp":1776887310000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11430692\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026]]},"references-count":52,"URL":"https:\/\/doi.org\/10.1109\/tifs.2026.3673137","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026]]}}}