{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,27]],"date-time":"2026-01-27T23:30:31Z","timestamp":1769556631667,"version":"3.49.0"},"reference-count":47,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"2","license":[{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,3,1]],"date-time":"2022-03-01T00:00:00Z","timestamp":1646092800000},"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. Dependable and Secure Comput."],"published-print":{"date-parts":[[2022,3,1]]},"DOI":"10.1109\/tdsc.2020.3014390","type":"journal-article","created":{"date-parts":[[2020,8,5]],"date-time":"2020-08-05T20:54:56Z","timestamp":1596660896000},"page":"953-965","source":"Crossref","is-referenced-by-count":28,"title":["Defending Against Adversarial Attack Towards Deep Neural Networks Via Collaborative Multi-Task Training"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1388-7715","authenticated-orcid":false,"given":"Derui","family":"Wang","sequence":"first","affiliation":[{"name":"School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9118-5386","authenticated-orcid":false,"given":"Chaoran","family":"Li","sequence":"additional","affiliation":[{"name":"School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0655-666X","authenticated-orcid":false,"given":"Sheng","family":"Wen","sequence":"additional","affiliation":[{"name":"School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3289-6599","authenticated-orcid":false,"given":"Surya","family":"Nepal","sequence":"additional","affiliation":[{"name":"Data 61, CSRIO, Canberra, ACT, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5252-0831","authenticated-orcid":false,"given":"Yang","family":"Xiang","sequence":"additional","affiliation":[{"name":"School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, VIC, Australia"}]}],"member":"263","reference":[{"key":"ref1","first-page":"274","article-title":"Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples","volume-title":"Proc. 35th Int. Conf. Mach. Learn.","author":"Athalye"},{"key":"ref2","first-page":"284","article-title":"Synthesizing robust adversarial examples","author":"Athalye"},{"key":"ref3","article-title":"Adversarial patch","author":"Brown","year":"2017"},{"key":"ref4","article-title":"Thermometer encoding: One hot way to resist adversarial examples","author":"Buckman"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140444"},{"key":"ref6","article-title":"Magnet and","author":"Carlini","year":"2017"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref8","first-page":"854","article-title":"Parseval networks: Improving robustness to adversarial examples","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Cisse"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/P18-2006"},{"key":"ref10","first-page":"1802","article-title":"A rotation and a translation suffice: Fooling CNNs with simple transformations","author":"Engstrom"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1145\/1014052.1014067"},{"key":"ref12","article-title":"Detecting adversarial samples from artifacts","author":"Feinman","year":"2017"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2437384"},{"key":"ref14","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014","journal-title":"Comput. Sci."},{"key":"ref15","article-title":"On the (statistical) detection of adversarial examples","author":"Grosse","year":"2017"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66399-9_4"},{"key":"ref17","article-title":"Towards deep neural network architectures robust to adversarial examples","author":"Gu","year":"2015","journal-title":"Comput. Sci."},{"key":"ref18","article-title":"Countering adversarial images using input transformations","author":"Guo"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00681"},{"key":"ref20","first-page":"15","article-title":"Adversarial example defenses: ensembles of weak defenses are not strong","volume-title":"Proc. 11th USENIX Conf. Offensive Technol.","author":"He"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2018.00212"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/D17-1215"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1201\/9781351251389-8"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2015.7299170"},{"key":"ref25","article-title":"Delving into transferable adversarial examples and black-box attacks","author":"Liu","year":"2016"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.56"},{"key":"ref27","article-title":"Adversarial examples that fool detectors","author":"Lu","year":"2017"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.84"},{"key":"ref29","article-title":"Characterizing adversarial subspaces using local intrinsic dimensionality","author":"Ma","year":"2018"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.48550\/ARXIV.1706.06083"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1145\/3133956.3134057"},{"key":"ref32","article-title":"On detecting adversarial perturbations","volume-title":"Proc. IEEE Int. Conf. Learn. Representation","author":"Metzen"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3052973.3053009"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2016.41"},{"key":"ref38","article-title":"Foolbox v0. 8.0: A python toolbox to benchmark the robustness of machine learning models","author":"Rauber","year":"2017"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3240765.3240791"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2018.04.027"},{"key":"ref41","article-title":"Pixeldefend: Leveraging generative models to understand and defend against adversarial examples","author":"Song","year":"2017"},{"key":"ref42","article-title":"Intriguing properties of neural networks","author":"Szegedy","year":"2013","journal-title":"Comput. Sci."},{"key":"ref43","article-title":"Ensemble adversarial training: Attacks and defenses","author":"Tram\u00e8r","year":"2017"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2020.3041481"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.153"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23198"},{"key":"ref47","first-page":"1829","article-title":"Defense against adversarial attacks using feature scattering-based adversarial training","volume-title":"Proc. Advances Neural Inf. Process. Syst.","author":"Zhang"}],"container-title":["IEEE Transactions on Dependable and Secure Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8858\/9733106\/09159878.pdf?arnumber=9159878","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T22:43:03Z","timestamp":1704840183000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9159878\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,3,1]]},"references-count":47,"journal-issue":{"issue":"2"},"URL":"https:\/\/doi.org\/10.1109\/tdsc.2020.3014390","relation":{},"ISSN":["1545-5971","1941-0018","2160-9209"],"issn-type":[{"value":"1545-5971","type":"print"},{"value":"1941-0018","type":"electronic"},{"value":"2160-9209","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,3,1]]}}}