{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,1]],"date-time":"2026-05-01T13:57:56Z","timestamp":1777643876832,"version":"3.51.4"},"reference-count":57,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"5","license":[{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,10,1]],"date-time":"2024-10-01T00:00:00Z","timestamp":1727740800000},"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":["62102105"],"award-info":[{"award-number":["62102105"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2022A1515011501"],"award-info":[{"award-number":["2022A1515011501"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100021171","name":"Basic and Applied Basic Research Foundation of Guangdong Province","doi-asserted-by":"publisher","award":["2022A1515010138"],"award-info":[{"award-number":["2022A1515010138"]}],"id":[{"id":"10.13039\/501100021171","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Science and Technology Program of Guangzhou","award":["202201020229"],"award-info":[{"award-number":["202201020229"]}]},{"name":"Program of Guangzhou University","award":["YJ2023048"],"award-info":[{"award-number":["YJ2023048"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Emerg. Top. Comput. Intell."],"published-print":{"date-parts":[[2024,10]]},"DOI":"10.1109\/tetci.2024.3378652","type":"journal-article","created":{"date-parts":[[2024,3,29]],"date-time":"2024-03-29T18:26:03Z","timestamp":1711736763000},"page":"3396-3407","source":"Crossref","is-referenced-by-count":10,"title":["Effective Single-Step Adversarial Training With Energy-Based Models"],"prefix":"10.1109","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0377-1022","authenticated-orcid":false,"given":"Keke","family":"Tang","sequence":"first","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5325-3445","authenticated-orcid":false,"given":"Tianrui","family":"Lou","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Technology, Sun Yat-sen University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5820-889X","authenticated-orcid":false,"given":"Weilong","family":"Peng","sequence":"additional","affiliation":[{"name":"School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3104-3017","authenticated-orcid":false,"given":"Nenglun","family":"Chen","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3580-0652","authenticated-orcid":false,"given":"Yawen","family":"Shi","sequence":"additional","affiliation":[{"name":"Cyberspace Institute of Advanced Technology, Guangzhou University, Guangzhou, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2284-3952","authenticated-orcid":false,"given":"Wenping","family":"Wang","sequence":"additional","affiliation":[{"name":"Department of Computer Science & Engineering, Texas A&M University, College Station, TX, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref3","first-page":"1","article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Simonyan","year":"2015"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2022.3196129"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref6","first-page":"1","article-title":"Intriguing properties of neural networks","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Szegedy","year":"2014"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25338"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1145\/3583780.3615198"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2021.3111024"},{"key":"ref10","first-page":"124","article-title":"Learning density distribution of reachable states for autonomous systems","volume-title":"Proc. Conf. Robot Learn.","author":"Meng","year":"2022"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/70.285583"},{"key":"ref12","first-page":"1","article-title":"Characterizing adversarial subspaces using local intrinsic dimensionality","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Ma","year":"2018"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58604-1_45"},{"key":"ref14","first-page":"1","article-title":"Explaining and harnessing adversarial examples","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Goodfellow","year":"2015"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.06083"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-40283-8_28"},{"key":"ref17","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhang","year":"2019"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v35i9.16989"},{"key":"ref19","first-page":"1","article-title":"Fast is better than free: Revisiting adversarial training","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wong","year":"2019"},{"key":"ref20","first-page":"3358","article-title":"Adversarial training for free!","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Shafahi","year":"2019"},{"key":"ref21","first-page":"1","article-title":"You only propagate once: Accelerating adversarial training via maximal principle","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Zhang","year":"2019"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1609.03126"},{"key":"ref23","first-page":"1","article-title":"Adversarial machine learning at scale","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Kurakin","year":"2017"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00957"},{"key":"ref25","first-page":"1","article-title":"Decision-based adversarial attacks: Reliable attacks against black-box machine learning models","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Brendel","year":"2018"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140448"},{"key":"ref27","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Croce","year":"2020"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2886017"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1049\/cit2.12028"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1016\/j.eng.2019.12.012"},{"key":"ref31","first-page":"1","article-title":"Countering adversarial images using input transformations","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Guo","year":"2018"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00126"},{"key":"ref33","first-page":"1","article-title":"Ensemble adversarial training: Attacks and defenses","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Tramr","year":"2018"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01305"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00103"},{"key":"ref36","first-page":"1","article-title":"Understanding and improving fast adversarial training","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Andriushchenko","year":"2020"},{"key":"ref37","first-page":"20297","article-title":"Guided adversarial attack for evaluating and enhancing adversarial defenses","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Sriramanan","year":"2020"},{"key":"ref38","first-page":"11821","article-title":"Towards efficient and effective adversarial training","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Sriramanan","year":"2021"},{"key":"ref39","first-page":"12881","article-title":"Make some noise: Reliable and efficient single-step adversarial training","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Aranda","year":"2022"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i6.20571"},{"key":"ref41","first-page":"1","article-title":"A tutorial on energy-based learning","volume":"1","author":"LeCun","year":"2006","journal-title":"Predicting Structured Data"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.79.8.2554.PMC346238.PMID6953413"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.119"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2018.2879081"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00900"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2019.2934852"},{"key":"ref47","first-page":"1","article-title":"A unified contrastive energy-based model for understanding the generative ability of adversarial training","volume-title":"Proc. Int. Conf. Learn. Representations","author":"Wang","year":"2022"},{"key":"ref48","first-page":"1100","article-title":"Deep structured energy based models for anomaly detection","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Zhai","year":"2016"},{"key":"ref49","first-page":"1","article-title":"Energy-based out-of-distribution detection","volume-title":"Proc. Annu. Conf. Neural Inf. Process. Syst.","author":"Liu","year":"2020"},{"key":"ref50","article-title":"Distilling the knowledge in a neural network","author":"Hinton","year":"2015"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00489"},{"key":"ref52","article-title":"Learning multiple layers of features from tiny images","author":"Krizhevsky","year":"2009"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.5244\/C.30.87"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01060"},{"issue":"11","key":"ref56","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref57","first-page":"274","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Athalye","year":"2018"}],"container-title":["IEEE Transactions on Emerging Topics in Computational Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/7433297\/10703967\/10485467.pdf?arnumber=10485467","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,11,26]],"date-time":"2024-11-26T18:56:56Z","timestamp":1732647416000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10485467\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,10]]},"references-count":57,"journal-issue":{"issue":"5"},"URL":"https:\/\/doi.org\/10.1109\/tetci.2024.3378652","relation":{},"ISSN":["2471-285X"],"issn-type":[{"value":"2471-285X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,10]]}}}