{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T21:06:18Z","timestamp":1780434378776,"version":"3.54.1"},"reference-count":114,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"6","license":[{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,6,1]],"date-time":"2026-06-01T00:00:00Z","timestamp":1780272000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/100006602","name":"Air Force Research Laboratory","doi-asserted-by":"crossref","award":["FA8750-23-C-0085"],"award-info":[{"award-number":["FA8750-23-C-0085"]}],"id":[{"id":"10.13039\/100006602","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Artif. Intell."],"published-print":{"date-parts":[[2026,6]]},"DOI":"10.1109\/tai.2025.3641908","type":"journal-article","created":{"date-parts":[[2025,12,9]],"date-time":"2025-12-09T18:36:16Z","timestamp":1765305376000},"page":"3050-3067","source":"Crossref","is-referenced-by-count":1,"title":["Contrast Duality of Adversarial Learningin Network Intrusion: A Review"],"prefix":"10.1109","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1705-0587","authenticated-orcid":false,"given":"Shalini","family":"Saini","sequence":"first","affiliation":[{"name":"Texas A&M University-Central Texas, Killeen, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8035-1761","authenticated-orcid":false,"given":"Anitha","family":"Chennamaneni","sequence":"additional","affiliation":[{"name":"Subhani Department of Computer Information Systems, Texas A&M University-Central Texas, Killeen, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3277-5519","authenticated-orcid":false,"given":"Babatunde","family":"Sawyerr","sequence":"additional","affiliation":[{"name":"Computer Science Department, University of Lagos, Lagos, Nigeria"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref5","article-title":"Why is cybersecurity important?","year":"2021"},{"key":"ref7","article-title":"Gartner forecasts global security and risk management spending to grow 14% in 2024","year":"2023"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1016\/j.comcom.2022.09.012"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/NFV-SDN47374.2019.9040101"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2661829.2662047"},{"key":"ref11","article-title":"Adversarial machine learning in network intrusion detection domain: A systematic review","author":"Alatwi","year":"2021"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2019.105124"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.3390\/fi15020062"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/ISTAS50296.2020.9462227"},{"issue":"7","key":"ref15","first-page":"62","article-title":"A review of big data in network intrusion detection system: Challenges, approaches, datasets, and tools","volume-title":"J. Comput. Sci. Eng.","volume":"8","author":"Alshamy","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ACCAI53970.2022.9752526"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/WCRE.2011.28"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3469659"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3301451"},{"key":"ref20","first-page":"284","article-title":"Synthesizing robust adversarial examples","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Athalye","year":"2018"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/BigDataSecurity-HPSC-IDS.2016.60"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/CISS48834.2020.1570617116"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/591"},{"key":"ref24","article-title":"Malicious packet classification based on neural network using Kitsune features","volume-title":"Proc. Intell. Syst. Pattern Recogn.: Second Int. Conf. (ISPR)","author":"Ban","year":"2022"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40994-3_25"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.023"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103676"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TR.2021.3105697"},{"key":"ref29","article-title":"On evaluating adversarial robustness","author":"Carlini","year":"2019"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.12028"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2021.3080522"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3385003.3410925"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2020.3041793"},{"key":"ref34","first-page":"1310","article-title":"Certified adversarial robustness via randomized smoothing","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Cohen","year":"2019"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2022.08.011"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103176"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.3390\/app10103559"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.9734\/ajrcos\/2021\/v7i430185"},{"key":"ref39","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2021.3087242"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2022.3233793"},{"key":"ref42","article-title":"Liuer Mihou: A practical framework for generating and evaluating grey-box adversarial attacks against NIDS","author":"He","year":"2022"},{"key":"ref43","first-page":"2921","article-title":"Fooling neural network interpretations via adversarial model manipulation","volume":"32","author":"Heo","year":"2019","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1145\/3712307"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.37256\/jeee.4120255738"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/ICDSIC56987.2022.10076144"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.4108\/eai.3-12-2015.2262516"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1016\/j.comnet.2022.109073"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1155\/2022\/4016073"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TWC.2021.3124855"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.3390\/app13052754"},{"key":"ref52","article-title":"Reverse engineering of network signatures","volume-title":"Proc. AusCERT Asia Pacific Inf. Technol. Secur. Conf.","author":"Kruegel","year":"2005"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1145\/3339252.3339266"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103205"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1080\/00031305.2021.2006781"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00035"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.3390\/app9204396"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1109\/ISVLSI.2019.00122"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.3390\/jcp2010010"},{"key":"ref60","article-title":"Black-box model inversion attribute inference attacks on classification models","author":"Mehnaz","year":"2020"},{"key":"ref61","doi-asserted-by":"publisher","DOI":"10.1109\/ICCVW.2017.94"},{"key":"ref62","doi-asserted-by":"publisher","DOI":"10.1007\/s12243-022-00910-1"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/SoutheastCon48659.2022.9763941"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2020.2970615"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23204"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2871719"},{"key":"ref67","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2021.3083060"},{"key":"ref68","first-page":"5233","article-title":"All you need to know about,\u201d {\u201cOn-Device,\u201d} {ML} \u201cmodel extraction-the gap between research and practice","volume-title":"Proc. 33rd USENIX Secur. Symp. (USENIX Secur.)","author":"Nayan","year":"2024"},{"key":"ref69","doi-asserted-by":"publisher","DOI":"10.3390\/s23135941"},{"key":"ref70","doi-asserted-by":"publisher","DOI":"10.1109\/INFOCOM42981.2021.9488902"},{"key":"ref71","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref72","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref73","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-13453-2_1"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2020.04.013"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1002\/nem.2050"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00073"},{"issue":"3","key":"ref77","first-page":"580","article-title":"Rev. Kdd Cup \u201899, Nsl-Kdd Kyoto 2006+ Datasets. Vojnotehni\u010dki Glasnik\/Mil","volume":"66","author":"Proti\u0107","year":"2018","journal-title":"Tech. Courier,"},{"key":"ref78","first-page":"361","article-title":"Flow-based benchmark data sets for intrusion detection","volume-title":"Proc. 16th Eur. Conf. Cyber Warfare Security","author":"Ring","year":"2017"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2019.06.005"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.1145\/3453158"},{"key":"ref81","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2021.3052888"},{"key":"ref82","article-title":"Predatory medicine: Exploring and measuring the vulnerability of medical AI to predatory science","author":"Saini","year":"2022"},{"key":"ref83","doi-asserted-by":"publisher","DOI":"10.1007\/s11036-021-01843-0"},{"key":"ref85","first-page":"9389","article-title":"Just how toxic is data poisoning? a unified benchmark for backdoor and data poisoning attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Schwarzschild","year":"2021"},{"key":"ref86","first-page":"1487","article-title":"Explanation-guided","volume-title":"Proc. 30th USENIX Security Symp. (USENIX Security)","author":"Severi","year":"2021"},{"key":"ref87","first-page":"6103","article-title":"Poison frogs! targeted clean-label poisoning attacks on neural networks","volume":"31","author":"Shafahi","year":"2018","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"ref88","article-title":"The sunburst hack was massive and devastating","author":"Shakarian","year":"2021"},{"key":"ref89","doi-asserted-by":"publisher","DOI":"10.5220\/0006639801080116"},{"key":"ref90","doi-asserted-by":"publisher","DOI":"10.1109\/CCST.2019.8888419"},{"key":"ref91","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM.2017.8170807"},{"key":"ref92","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2011.12.012"},{"key":"ref93","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2017.2772792"},{"key":"ref94","doi-asserted-by":"publisher","DOI":"10.1145\/1978672.1978676"},{"key":"ref95","article-title":"Percentage of global population accessing the internet by April 2024","year":"(2024)"},{"key":"ref96","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2021.3130903"},{"key":"ref97","article-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2013"},{"key":"ref98","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM52596.2021.9652959"},{"key":"ref99","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref100","doi-asserted-by":"publisher","DOI":"10.1016\/j.procs.2020.03.330"},{"key":"ref101","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58951-6_24"},{"key":"ref102","article-title":"Ensemble adversarial training: attacks and defenses","author":"Tram\u00e8r","year":"2017"},{"key":"ref103","doi-asserted-by":"publisher","DOI":"10.1109\/IJCNN48605.2020.9207472"},{"key":"ref104","doi-asserted-by":"publisher","DOI":"10.1109\/MILCOM52596.2021.9652916"},{"key":"ref105","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2023.103433"},{"key":"ref106","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"ref107","doi-asserted-by":"publisher","DOI":"10.13052\/jwe1540-9589.2059"},{"key":"ref108","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8682578"},{"key":"ref109","first-page":"10859","article-title":"Robust learning for data poisoning attacks","volume-title":"Proc. Int. Conf. Mach. Learn. (PMLR)","author":"Wang","year":"2021"},{"key":"ref110","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2019.2929047"},{"key":"ref111","doi-asserted-by":"publisher","DOI":"10.7551\/mitpress\/10761.003.0012"},{"key":"ref112","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102280"},{"key":"ref113","article-title":"Targeted poisoning attacks on black-box neural machine translation","author":"Xu","year":"2020"},{"key":"ref114","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-019-1211-x"},{"key":"ref115","doi-asserted-by":"publisher","DOI":"10.1109\/WF-IoT48130.2020.9221383"},{"key":"ref116","doi-asserted-by":"publisher","DOI":"10.1145\/3411495.3421359"},{"key":"ref117","doi-asserted-by":"publisher","DOI":"10.1109\/TNET.2021.3137084"},{"key":"ref118","doi-asserted-by":"publisher","DOI":"10.1145\/3374217"},{"key":"ref119","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2020.12.042"},{"key":"ref120","doi-asserted-by":"publisher","DOI":"10.1145\/3547330"}],"container-title":["IEEE Transactions on Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/9078688\/11541276\/11285783.pdf?arnumber=11285783","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T20:10:13Z","timestamp":1780431013000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11285783\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,6]]},"references-count":114,"journal-issue":{"issue":"6"},"URL":"https:\/\/doi.org\/10.1109\/tai.2025.3641908","relation":{},"ISSN":["2691-4581"],"issn-type":[{"value":"2691-4581","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,6]]}}}