{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T20:05:31Z","timestamp":1784318731317,"version":"3.55.0"},"reference-count":30,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","issue":"4","license":[{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,1]],"date-time":"2026-08-01T00:00:00Z","timestamp":1785542400000},"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 Des. Test"],"published-print":{"date-parts":[[2026,8]]},"DOI":"10.1109\/mdat.2025.3637710","type":"journal-article","created":{"date-parts":[[2025,11,26]],"date-time":"2025-11-26T19:05:00Z","timestamp":1764183900000},"page":"8-24","source":"Crossref","is-referenced-by-count":1,"title":["The Fault in Our Chips: A Survey on Edge AI Accelerator Vulnerabilities"],"prefix":"10.1109","volume":"43","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5992-8554","authenticated-orcid":false,"given":"Shamik","family":"Kundu","sequence":"first","affiliation":[{"name":"Advanced Architecture Research Group, Intel Corporation, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0005-4259-1915","authenticated-orcid":false,"given":"Sanjay","family":"Das","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-1049-3036","authenticated-orcid":false,"given":"Anand","family":"Menon","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2904-9388","authenticated-orcid":false,"given":"Swastik","family":"Bhattacharya","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8848-1069","authenticated-orcid":false,"given":"Arnab","family":"Raha","sequence":"additional","affiliation":[{"name":"Advanced Architecture Research Group, Intel Corporation, Santa Clara, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6431-7512","authenticated-orcid":false,"given":"Kanad","family":"Basu","sequence":"additional","affiliation":[{"name":"Department of Electrical and Computer Engineering, The University of Texas at Dallas, Richardson, TX, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"Towards functional safety in deep learning hardware accelerators","author":"Kundu","year":"2024"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1145\/3458336.3465297"},{"key":"ref3","article-title":"The llama 3 herd of models","author":"Grattafiori","year":"2024","journal-title":"arXiv:2407.21783"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/MDAT.2023.3241116"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2022.3217841"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/3638242"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1016\/j.sysarc.2019.101689"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00130"},{"key":"ref9","article-title":"AttentionBreaker: Adaptive evolutionary optimization for unmasking vulnerabilities in LLMs through bit-flip attacks","author":"Das","year":"2024","journal-title":"arXiv:2411.13757"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1587\/elex.10.20130743"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/MDAT.2022.3174181"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/DDECS54261.2022.9770168"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.microrel.2022.114666"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/VTS52500.2021.9794227"},{"key":"ref15","first-page":"349","article-title":"GuardNN: Secure accelerator architecture for privacy-preserving deep learning","volume-title":"Proc. 59th ACM\/IEEE Design Autom. Conf.","author":"Hua"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1109\/ICSE43902.2021.00044"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/HOST55342.2024.10545413"},{"key":"ref18","first-page":"1","article-title":"MENDNet: Just-in-time fault detection and mitigation in AI systems with uncertainty quantification and multi-exit networks","volume-title":"Proc. 61st ACM\/IEEE Design Autom. Conf.","author":"Kundu"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/DAC56929.2023.10247671"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2023.3236875"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2025.112805"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2021.3107401"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/DSN53405.2022.00024"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1109\/DFT59622.2023.10313535"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1145\/3445814.3446747"},{"key":"ref26","first-page":"203","article-title":"CheckFreq: Frequent, fine-grained DNN checkpointing","volume-title":"Proc. 19th USENIX Conf. File Storage Technol. (FAST)","author":"Mohan"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2019.2907248"},{"key":"ref28","first-page":"1","article-title":"Deep defense: Training DNNs with improved adversarial robustness","volume-title":"Proc.Adv. Neural Inf. Process. Syst.","volume":"31","author":"Yan"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.14313\/PAR_248\/89"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2022.3211411"}],"container-title":["IEEE Design &amp; Test"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6221038\/11613037\/11269794.pdf?arnumber=11269794","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,7,17]],"date-time":"2026-07-17T19:45:50Z","timestamp":1784317550000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11269794\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8]]},"references-count":30,"journal-issue":{"issue":"4"},"URL":"https:\/\/doi.org\/10.1109\/mdat.2025.3637710","relation":{},"ISSN":["2168-2356","2168-2364"],"issn-type":[{"value":"2168-2356","type":"print"},{"value":"2168-2364","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8]]}}}