{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,29]],"date-time":"2026-04-29T20:52:03Z","timestamp":1777495923260,"version":"3.51.4"},"reference-count":49,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"8","license":[{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2023,8,1]],"date-time":"2023-08-01T00:00:00Z","timestamp":1690848000000},"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":["62025601"],"award-info":[{"award-number":["62025601"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Cybern."],"published-print":{"date-parts":[[2023,8]]},"DOI":"10.1109\/tcyb.2022.3209175","type":"journal-article","created":{"date-parts":[[2022,10,14]],"date-time":"2022-10-14T20:19:29Z","timestamp":1665778769000},"page":"5323-5335","source":"Crossref","is-referenced-by-count":16,"title":["A Feature Space-Restricted Attention Attack on Medical Deep Learning Systems"],"prefix":"10.1109","volume":"53","author":[{"given":"Zizhou","family":"Wang","sequence":"first","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1457-6487","authenticated-orcid":false,"given":"Xin","family":"Shu","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3907-9388","authenticated-orcid":false,"given":"Yan","family":"Wang","sequence":"additional","affiliation":[{"name":"Institute of High Performance Computing, Agency for Science, Technology and Research, Fusionopolis, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yangqin","family":"Feng","sequence":"additional","affiliation":[{"name":"Institute of High Performance Computing, Agency for Science, Technology and Research, Fusionopolis, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9702-6738","authenticated-orcid":false,"given":"Lei","family":"Zhang","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5867-9322","authenticated-orcid":false,"given":"Zhang","family":"Yi","sequence":"additional","affiliation":[{"name":"College of Computer Science, Sichuan University, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v33i01.33011093"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2020.107332"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1136\/bmj.j5910"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00928-1_56"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.023"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1126\/science.aaw4399"},{"key":"ref17","article-title":"Adversarial attacks against medical deep learning systems","author":"finlayson","year":"2018","journal-title":"arXiv 1804 05296"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/S1359-6446(04)03334-3"},{"key":"ref19","first-page":"2642","article-title":"Conditional image synthesis with auxiliary classifier GANs","author":"odena","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/543"},{"key":"ref46","first-page":"2206","article-title":"Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks","author":"croce","year":"2020","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref45","article-title":"Ensemble adversarial training: Attacks and defenses","author":"tram\u00e8r","year":"2017","journal-title":"arXiv 1705 07204"},{"key":"ref48","article-title":"Stabilized medical image attacks","author":"qi","year":"2021","journal-title":"arXiv 2103 05232"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00041"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref41","first-page":"1","article-title":"The HAM10000 dataset, a large collection of multi-source dermatoscopic images of common pigmented skin lesions","volume":"5","author":"tschandl","year":"2018","journal-title":"Data Science Journal"},{"key":"ref44","first-page":"7472","article-title":"Theoretically principled trade-off between robustness and accuracy","author":"zhang","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.243"},{"key":"ref49","first-page":"274","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","author":"athalye","year":"2018","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.17438"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2019.2935141"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2020.3013489"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1136\/bmjqs-2013-002627"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1038\/s41591-018-0300-7"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2019.2963682"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3061147"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.369"},{"key":"ref35","first-page":"3519","article-title":"Similarity of neural network representations revisited","author":"kornblith","year":"2019","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1007\/BF00332918"},{"key":"ref37","article-title":"Adversarial examples are not bugs, they are features","author":"ilyas","year":"2019","journal-title":"arXiv 1905 02175"},{"key":"ref36","first-page":"214","article-title":"Wasserstein generative adversarial networks","author":"arjovsky","year":"2017","journal-title":"Proc Int Conf Mach Learn"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58592-1_29"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TEVC.2019.2890858"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00092"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/TCDS.2019.2900506"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2793911"},{"key":"ref39","article-title":"Labeled optical coherence tomography (OCT) and chest X-Ray images for classification","volume":"2","author":"kermany","year":"2018","journal-title":"Mendeley Data"},{"key":"ref38","year":"2019","journal-title":"APTOS 2019 Blindness Detection"},{"key":"ref24","first-page":"1","article-title":"Generative adversarial nets","volume":"27","author":"goodfellow","year":"2014","journal-title":"Proc Adv Neural Inf Process Syst"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2021.3071395"},{"key":"ref25","first-page":"1","article-title":"AdvGAN++: Harnessing latent layers for adversary generation","author":"mangla","year":"2019","journal-title":"Proc IEEE Int Conf Comput Vis Workshops"},{"key":"ref20","article-title":"Explaining and harnessing adversarial examples","author":"goodfellow","year":"2014","journal-title":"arXiv 1412 6572"},{"key":"ref22","article-title":"Towards deep learning models resistant to adversarial attacks","author":"madry","year":"2017","journal-title":"arXiv 1706 06083"},{"key":"ref21","article-title":"Adversarial examples in the physical world","author":"kurakin","year":"2016","journal-title":"arXiv 1607 02533"},{"key":"ref28","article-title":"Practical black-box attacks against deep learning systems using adversarial examples","author":"papernot","year":"2016","journal-title":"arXiv 1602 02697"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2022.3146388"},{"key":"ref29","first-page":"2484","article-title":"Simple black-box adversarial attacks","author":"guo","year":"2019","journal-title":"Proc Int Conf Mach Learn"}],"container-title":["IEEE Transactions on Cybernetics"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/6221036\/10186010\/09919792.pdf?arnumber=9919792","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,7]],"date-time":"2023-08-07T18:22:11Z","timestamp":1691432531000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9919792\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8]]},"references-count":49,"journal-issue":{"issue":"8"},"URL":"https:\/\/doi.org\/10.1109\/tcyb.2022.3209175","relation":{},"ISSN":["2168-2267","2168-2275"],"issn-type":[{"value":"2168-2267","type":"print"},{"value":"2168-2275","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8]]}}}