{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,6]],"date-time":"2026-03-06T07:07:17Z","timestamp":1772780837996,"version":"3.50.1"},"reference-count":34,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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. Serv. Comput."],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1109\/tsc.2023.3329081","type":"journal-article","created":{"date-parts":[[2023,11,13]],"date-time":"2023-11-13T19:22:21Z","timestamp":1699903341000},"page":"18-29","source":"Crossref","is-referenced-by-count":18,"title":["Resisting Deep Learning Models Against Adversarial Attack Transferability via Feature Randomization"],"prefix":"10.1109","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5714-8378","authenticated-orcid":false,"given":"Ehsan","family":"Nowroozi","sequence":"first","affiliation":[{"name":"Centre for Secure Information Technologies (CSIT), Queen&#x0027;s University Belfast (QUB), Belfast, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8470-3277","authenticated-orcid":false,"given":"Mohammadreza","family":"Mohammadi","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Security and Privacy Research Group (SPRITZ), University of Padua, Padua, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pargol","family":"Golmohammadi","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Security and Privacy Research Group (SPRITZ), University of Padua, Padua, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3860-8057","authenticated-orcid":false,"given":"Yassine","family":"Mekdad","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Cyber-Physical Systems Security Lab, Florida International University, Miami, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3612-1934","authenticated-orcid":false,"given":"Mauro","family":"Conti","sequence":"additional","affiliation":[{"name":"Department of Mathematics, Security and Privacy Research Group (SPRITZ), University of Padua, Padua, Italy"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9823-3464","authenticated-orcid":false,"given":"Selcuk","family":"Uluagac","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, Cyber-Physical Systems Security Lab, Florida International University, Miami, FL, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/EuroSP.2016.36"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/ACCESS.2018.2807385"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-981-15-9129-7_31"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1016\/j.cose.2020.102092"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2022.3225217"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3310273.3323072"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP.2019.8683772"},{"key":"ref8","article-title":"Feature randomization for improving the security of deep net in network security","author":"Nowroozi","year":"2022"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.3390\/jimaging7030050"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/b978-0-12-822109-9.00024-2"},{"key":"ref11","article-title":"Text adversarial attacks and defenses: Issues, taxonomy, and perspectives","volume":"2022","author":"Guo","year":"2022","journal-title":"Secur. Commun. Netw."},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-0716-2197-4_9"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3380446.3430628"},{"key":"ref14","article-title":"Mitigating adversarial effects through randomization","author":"Xie","year":"2017"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.01148"},{"key":"ref16","article-title":"Raid: Randomized adversarial-input detection for neural networks","author":"Eniser","year":"2020"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i3.20168"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TNSM.2022.3164354"},{"key":"ref19","article-title":"Towards deep learning models resistant to adversarial attacks","author":"Madry","year":"2017"},{"key":"ref20","article-title":"Intriguing properties of neural networks","volume-title":"Proc. 2nd Int. Conf. Learn. Representations","author":"Szegedy"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1201\/9781351251389-8"},{"key":"ref22","article-title":"Explaining and harnessing adversarial examples","author":"Goodfellow","year":"2014"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.282"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2018.2825953"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2018.8451698"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/2600918.2600941"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/MilCIS.2015.7348942"},{"key":"ref29","article-title":"Machine learning techniques for image forensics in adversarial setting","author":"Nowroozi","year":"2020"},{"key":"ref30","article-title":"Foolbox V0.8.0: A Python toolbox to benchmark the robustness of machine learning models","volume":"abs\/1707.0","author":"Rauber","year":"2017"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.23919\/EUSIPCO.2017.8081213"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-20320-6_11"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00453"}],"container-title":["IEEE Transactions on Services Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/4629386\/10422891\/10315205.pdf?arnumber=10315205","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T04:53:43Z","timestamp":1707281623000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10315205\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":34,"journal-issue":{"issue":"1"},"URL":"https:\/\/doi.org\/10.1109\/tsc.2023.3329081","relation":{},"ISSN":["1939-1374","2372-0204"],"issn-type":[{"value":"1939-1374","type":"electronic"},{"value":"2372-0204","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,1]]}}}