{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T05:10:44Z","timestamp":1754111444929,"version":"3.37.3"},"reference-count":42,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tifs.2022.3155975","type":"journal-article","created":{"date-parts":[[2022,3,2]],"date-time":"2022-03-02T20:28:57Z","timestamp":1646252937000},"page":"1099-1114","source":"Crossref","is-referenced-by-count":16,"title":["Adversarial Detection by Latent Style Transformations"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8938-2364","authenticated-orcid":false,"given":"Shuo","family":"Wang","sequence":"first","affiliation":[{"name":"CSIRO’s Data61 and Cybersecurity CRC, Marsfield, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3289-6599","authenticated-orcid":false,"given":"Surya","family":"Nepal","sequence":"additional","affiliation":[{"name":"CSIRO’s Data61 and Cybersecurity CRC, Marsfield, NSW, Australia"}]},{"given":"Alsharif","family":"Abuadbba","sequence":"additional","affiliation":[{"name":"CSIRO’s Data61 and Cybersecurity CRC, Marsfield, NSW, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9050-5675","authenticated-orcid":false,"given":"Carsten","family":"Rudolph","sequence":"additional","affiliation":[{"name":"Faculty of Information Technology, Monash University, Melbourne, Clayton, VIC, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6933-0145","authenticated-orcid":false,"given":"Marthie","family":"Grobler","sequence":"additional","affiliation":[{"name":"CSIRO’s Data61 and Cybersecurity CRC, Marsfield, NSW, Australia"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014","journal-title":"arXiv:1412.6572"},{"key":"ref2","article-title":"Defense-GAN: Protecting classifiers against adversarial attacks using generative models","author":"Samangouei","year":"2018","journal-title":"arXiv:1805.06605"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134057"},{"key":"ref4","article-title":"Featurized bidirectional GAN: Adversarial defense via adversarially learned semantic inference","author":"Bao","year":"2018","journal-title":"arXiv:1805.07862"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-010-5188-5"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1081870.1081950"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40994-3_25"},{"key":"ref8","article-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2013","journal-title":"arXiv:1312.6199"},{"key":"ref9","article-title":"The limitations of adversarial training and the blind-spot attack","author":"Zhang","year":"2019","journal-title":"arXiv:1901.04684"},{"key":"ref10","article-title":"Constructing unrestricted adversarial examples with generative models","author":"Song","year":"2018","journal-title":"arXiv:1805.07894"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11828"},{"key":"ref12","article-title":"Detecting adversarial examples via neural fingerprinting","author":"Dathathri","year":"2018","journal-title":"arXiv:1803.03870"},{"key":"ref13","first-page":"1","article-title":"Spatially transformed adversarial examples","volume-title":"Proc. 6th Int. Conf. Learn. Represent.","author":"Xiao"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00129"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00581"},{"key":"ref16","article-title":"GANSpace: Discovering interpretable GAN controls","author":"H\u00e4rk\u00f6nen","year":"2020","journal-title":"arXiv:2004.02546"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00926"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01267"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3450626.3459838"},{"key":"ref20","article-title":"Analyzing and improving the image quality of StyleGAN","author":"Karras","year":"2019","journal-title":"arXiv:1912.04958"},{"key":"ref21","first-page":"315","article-title":"Deep sparse rectifier neural networks","volume-title":"Proc. 14th Int. Conf. Artif. Intell. Statist.","author":"Glorot"},{"key":"ref22","article-title":"Adversarial feature learning","author":"Donahue","year":"2016","journal-title":"arXiv:1605.09782"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01411"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00068"},{"key":"ref25","article-title":"Adversarial example detection and classification with asymmetrical adversarial training","author":"Yin","year":"2019","journal-title":"arXiv:1905.11475"},{"key":"ref26","article-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2017","journal-title":"arXiv:1706.06083"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref28","article-title":"LSUN: Construction of a large-scale image dataset using deep learning with humans in the loop","author":"Yu","year":"2015","journal-title":"arXiv:1506.03365"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref31","article-title":"Very deep convolutional networks for large-scale image recognition","author":"Simonyan","year":"2014","journal-title":"arXiv:1409.1556"},{"key":"ref32","article-title":"Adversarial machine learning at scale","author":"Kurakin","year":"2016","journal-title":"arXiv:1611.01236"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00957"},{"key":"ref35","article-title":"Foolbox: A Python toolbox to benchmark the robustness of machine learning models","author":"Rauber","year":"2017","journal-title":"arXiv:1707.04131"},{"key":"ref36","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014","journal-title":"arXiv:1412.6572"},{"key":"ref37","article-title":"Beneficial perturbations network for defending adversarial examples","author":"Wen","year":"2020","journal-title":"arXiv:2009.12724"},{"key":"ref38","first-page":"284","article-title":"Synthesizing robust adversarial examples","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Athalye"},{"key":"ref39","article-title":"On adaptive attacks to adversarial example defenses","author":"Tramer","year":"2020","journal-title":"arXiv:2002.08347"},{"key":"ref40","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","author":"Athalye","year":"2018","journal-title":"arXiv:1802.00420"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2886017"},{"key":"ref42","first-page":"8921","article-title":"Adversarial example games","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Bose"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/9652463\/09724182.pdf?arnumber=9724182","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,12]],"date-time":"2024-01-12T00:24:05Z","timestamp":1705019045000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9724182\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":42,"URL":"https:\/\/doi.org\/10.1109\/tifs.2022.3155975","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"type":"print","value":"1556-6013"},{"type":"electronic","value":"1556-6021"}],"subject":[],"published":{"date-parts":[[2022]]}}}