{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,5]],"date-time":"2026-09-05T16:48:25Z","timestamp":1788626905547,"version":"build-2803163510"},"reference-count":65,"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"}],"funder":[{"DOI":"10.13039\/501100005357","name":"Agentra na Podporu Vskumu a Vvoja","doi-asserted-by":"publisher","award":["SK-SRB-21-0059"],"award-info":[{"award-number":["SK-SRB-21-0059"]}],"id":[{"id":"10.13039\/501100005357","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100010783","name":"Slovensk Akadmia Vied","doi-asserted-by":"publisher","award":["SASPRO 2 COFUND Marie Sklodowska-Curie grant agree"],"award-info":[{"award-number":["SASPRO 2 COFUND Marie Sklodowska-Curie grant agree"]}],"id":[{"id":"10.13039\/100010783","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans. Dependable and Secure Comput."],"published-print":{"date-parts":[[2022]]},"DOI":"10.1109\/tdsc.2022.3166671","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T19:33:14Z","timestamp":1649791994000},"page":"1-1","source":"Crossref","is-referenced-by-count":12,"title":["FooBaR: Fault Fooling Backdoor Attack on Neural Network Training"],"prefix":"10.1109","author":[{"given":"Jakub","family":"Breier","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaolu","family":"Hou","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Martin","family":"Ochoa","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jesus","family":"Solano","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-11333-9"},{"key":"ref57","article-title":"Intriguing properties of neural networks","author":"szegedy","year":"2013"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.46586\/tches.v2019.i2.199-224"},{"key":"ref56","article-title":"Intriguing properties of neural networks","author":"szegedy","year":"2013"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/2818362.2818367"},{"key":"ref59","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3278519"},{"key":"ref58","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-21040-2_15"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01321"},{"key":"ref52","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354201"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/SYSOSE.2017.7994971"},{"key":"ref55","article-title":"Very deep convolutional networks for large-scale image recognition","author":"simonyan","year":"2014"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2018.07.023"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-29726-8_18"},{"key":"ref17","article-title":"SNIFF: Reverse engineering of neural networks with fault attacks","author":"breier","year":"2020"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/2732198.2732206"},{"key":"ref19","article-title":"Targeted backdoor attacks on deep learning systems using data poisoning","author":"chen","year":"2017"},{"key":"ref18","article-title":"Detecting backdoor attacks on deep neural networks by activation clustering","author":"chen","year":"2018"},{"key":"ref51","first-page":"231","article-title":"Lightweight fault attack resistance in software using intra-instruction redundancy","author":"patrick","year":"2016","journal-title":"Proc Int Conf Sel Areas Cryptogr"},{"key":"ref50","article-title":"Practical black-box attacks against deep learning systems using adversarial examples","author":"papernot","year":"2016"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3128572.3140451"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1007\/s13389-014-0077-7"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW.2017.172"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/MSEC.2020.2990495"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203770"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-00470-5_13"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2018.23291"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3363216"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1145\/322276.322287"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-40994-3_25"},{"key":"ref7","first-page":"515","article-title":"CSINN: Reverse engineering of neural network architectures through electromagnetic side channel","author":"batina","year":"2019","journal-title":"Proc 28th USENIX Secur Symp"},{"key":"ref9","article-title":"Poisoning attacks against support vector machines","author":"biggio","year":"2012"},{"key":"ref4","article-title":"Fault attacks in symmetric key cryptosystems","author":"baksi","year":"2020"},{"key":"ref3","article-title":"Targeted attack against deep neural networks via flipping limited weight bits","author":"bai","year":"2021"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/1873548.1873555"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66787-4_16"},{"key":"ref40","article-title":"Backdoor embedding in convolutional neural network models via invisible perturbation","author":"liao","year":"2018"},{"key":"ref35","first-page":"1097","article-title":"ImageNet classification with deep convolutional neural networks","author":"krizhevsky","year":"2012","journal-title":"Proc 25th Int Conf Neural Inf Process Syst"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.46586\/tches.v2018.i3.44-68"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/MNET.2018.1700202"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/5.726791"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-29656-7"},{"key":"ref30","article-title":"BadEncoder: Backdoor attacks to pre-trained encoders in self-supervised learning","author":"jia","year":"2021"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-50127-7_11"},{"key":"ref32","first-page":"1445","article-title":"V0LTpwn: Attacking x86 processor integrity from software","author":"kenjar","year":"2020","journal-title":"Proc 29th USENIX Secur Symp"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-66787-4_9"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/ICEngTechnol.2017.8308186"},{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2021.07.051"},{"key":"ref38","article-title":"Backdoor learning: A survey","author":"li","year":"2020"},{"key":"ref24","article-title":"An overview of backdoor attacks against deep neural networks and possible defences","author":"guo","year":"2021"},{"key":"ref23","article-title":"BadNets: Identifying vulnerabilities in the machine learning model supply chain","author":"gu","year":"2017"},{"key":"ref26","first-page":"497","article-title":"Terminal brain damage: Exposing the graceless degradation in deep neural networks under hardware fault attacks","author":"hong","year":"2019","journal-title":"Proc 28th USENIX Secur Symp"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1016\/B978-0-12-741252-8.50010-8"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2012.2211477"},{"key":"ref64","doi-asserted-by":"publisher","DOI":"10.1145\/3450569.3463560"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1145\/3394885.3431639"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-40667-1_15"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom45495.2020.9127389"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1145\/3316781.3317825"},{"key":"ref28","article-title":"High-fidelity extraction of neural network models","author":"jagielski","year":"2019"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2021.114116"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.4108\/eai.3-12-2015.2262516"},{"key":"ref60","first-page":"1281","article-title":"With great training comes great vulnerability: Practical attacks against transfer learning","author":"wang","year":"2018","journal-title":"Proc 27th USENIX Secur Symp"},{"key":"ref62","first-page":"1689","article-title":"Is feature selection secure against training data poisoning?","author":"xiao","year":"2015","journal-title":"Proc 32nd Int Conf Mach Learn"},{"key":"ref61","article-title":"Data poisoning attacks against online learning","author":"wang","year":"2018"}],"container-title":["IEEE Transactions on Dependable and Secure Computing"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8858\/4358699\/09756234.pdf?arnumber=9756234","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T20:30:27Z","timestamp":1684269027000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9756234\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"references-count":65,"URL":"https:\/\/doi.org\/10.1109\/tdsc.2022.3166671","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]]}}}