{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T12:45:56Z","timestamp":1752669956175,"version":"3.37.3"},"reference-count":28,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"name":"the Science and Technology Development Plan Project of Jilin Province","award":["20200404216YY"],"award-info":[{"award-number":["20200404216YY"]}]},{"name":"the Science and Technology Development Program of Jilin Province","award":["20200401066GX"],"award-info":[{"award-number":["20200401066GX"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U2141231"],"award-info":[{"award-number":["U2141231"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2023]]},"DOI":"10.1109\/access.2023.3280421","type":"journal-article","created":{"date-parts":[[2023,5,26]],"date-time":"2023-05-26T17:48:03Z","timestamp":1685123283000},"page":"1-1","source":"Crossref","is-referenced-by-count":4,"title":["AEC_GAN: Unbalanced Data Processing Decision-Making in Network Attacks Based on ACGAN and Machine Learning"],"prefix":"10.1109","author":[{"given":"Naibo","family":"Zhu","sequence":"first","affiliation":[{"name":"Unit 32801 of the Chinese People&#x2019;s Liberation Army, Beijing, China"}]},{"given":"Guangyu","family":"Zhao","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6511-3079","authenticated-orcid":false,"given":"Yang","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3263-6498","authenticated-orcid":false,"given":"Han","family":"Yang","sequence":"additional","affiliation":[{"name":"Beijing Engineering Research Center of Emergency Survival Security, Beijing, China"}]},{"given":"Zhi","family":"Liu","sequence":"additional","affiliation":[{"name":"School of Electronic Information Engineering, Changchun University of Science and Technology, Changchun, China"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2927465"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2933165"},{"key":"ref15","article-title":"Conditional image synthesis with auxiliary classifier GANs","author":"odena","year":"2016","journal-title":"arXiv 1610 09585"},{"key":"ref14","article-title":"Unsupervised representation learning with deep convolutional generative adversarial networks","author":"radford","year":"2015","journal-title":"arXiv 1511 06434"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2019.2904620"},{"key":"ref10","first-page":"90","article-title":"Multiscale convolutional CNN model for network intrusion detection","volume":"55","author":"liu","year":"2019","journal-title":"Comput Eng Appl"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.3390\/app9204221"},{"journal-title":"Computer Security Threat Monitoring and Surveillance","year":"1980","author":"anderson","key":"ref1"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref16","article-title":"Adam: A method for stochastic optimization","author":"kingma","year":"2014","journal-title":"arXiv 1412 6980"},{"key":"ref19","first-page":"1","article-title":"Network intrusion detection based on Tianniu herd optimization and improvement of regularized limit learning machine","author":"zhendong","year":"2022","journal-title":"Journal of Automatica"},{"journal-title":"NSL-KDD Dataset","year":"0","key":"ref18"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2021.102289"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2017.2762418"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2016.09.041"},{"key":"ref25","article-title":"Intrusion detection model based on deep belief network","volume":"2","author":"kunpeng","year":"2015","journal-title":"Modern Comput Pro Ed"},{"key":"ref20","volume":"3","author":"mingzhao","year":"2020","journal-title":"Research on Intrusion Detection Technology Based on Machine Learning"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TETCI.2017.2772792"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/ICUFN.2018.8436774"},{"key":"ref28","volume":"9","author":"hao","year":"2021","journal-title":"Research on Intrusion Detection Algorithm Based on Optimized Convolutional Neural Network"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2867564"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1161\/CIRCOUTCOMES.118.005122"},{"key":"ref7","volume":"5","author":"daozhou","year":"2019","journal-title":"Design and Implementation of Network Intrusion Detection System Based on Linux Platform"},{"key":"ref9","first-page":"2672","article-title":"Generative adversarial networks","author":"goodfellow","year":"2014","journal-title":"Proc Neural Inf Process Syst"},{"key":"ref4","first-page":"875","article-title":"Optimize intrusion detection of BP neural networks with improved gray wolf algorithms","volume":"42","author":"zhendong","year":"2021","journal-title":"Small Microcomput Syst"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2868993"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1002\/dac.3547"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1016\/j.inffus.2021.02.007"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6287639\/6514899\/10136726.pdf?arnumber=10136726","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,6]],"date-time":"2023-06-06T23:13:04Z","timestamp":1686093184000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10136726\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"references-count":28,"URL":"https:\/\/doi.org\/10.1109\/access.2023.3280421","relation":{},"ISSN":["2169-3536"],"issn-type":[{"type":"electronic","value":"2169-3536"}],"subject":[],"published":{"date-parts":[[2023]]}}}