{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T13:25:51Z","timestamp":1740144351850,"version":"3.37.3"},"reference-count":55,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001381","name":"National Research Foundation, Singapore, through the National Cybersecurity R&D Programme\/Cyber-Hardware Forensic & Assurance Evaluation R&D Programme","doi-asserted-by":"publisher","award":["CHFA-GC1-AW01"],"award-info":[{"award-number":["CHFA-GC1-AW01"]}],"id":[{"id":"10.13039\/501100001381","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key R&D Program of China","award":["2020AAA0107700"],"award-info":[{"award-number":["2020AAA0107700"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62072398"],"award-info":[{"award-number":["62072398"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Zhejiang Key R&D Plan","award":["2019C03133"],"award-info":[{"award-number":["2019C03133"]}]},{"name":"Alibaba-Zhejiang University Joint Institute of Frontier Technologies"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2021]]},"DOI":"10.1109\/tifs.2020.3046858","type":"journal-article","created":{"date-parts":[[2020,12,23]],"date-time":"2020-12-23T20:27:39Z","timestamp":1608755259000},"page":"1928-1942","source":"Crossref","is-referenced-by-count":5,"title":["Stealthy and Robust Glitch Injection Attack on Deep Learning Accelerator for Target With Variational Viewpoint"],"prefix":"10.1109","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4590-5367","authenticated-orcid":false,"given":"Wenye","family":"Liu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8897-6176","authenticated-orcid":false,"given":"Chip-Hong","family":"Chang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6087-8243","authenticated-orcid":false,"given":"Fan","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref39","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354201"},{"key":"ref38","first-page":"1057","article-title":"CLKSCREW: Exposing the perils of security-oblivious energy management","author":"tang","year":"2017","journal-title":"Proc 26th USENIX Secur Symp"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2636225"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3079856.3080246"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/JSSC.2016.2616357"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1038\/nature14539","article-title":"Deep learning","volume":"521","author":"lecun","year":"2015","journal-title":"Nature"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-12510-2_13"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.17"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TVLSI.2018.2815603"},{"journal-title":"DPU for Convolutional Neural Network v3 0","year":"2019","key":"ref34"},{"article-title":"Very deep convolutional networks for large-scale image recognition","year":"0","author":"simonyan","key":"ref28"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00474"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1023\/B:VISI.0000042993.50813.60"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2017.2761740"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2019.2918951"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.23919\/DATE.2019.8715027"},{"key":"ref22","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":"ref21","doi-asserted-by":"publisher","DOI":"10.1109\/FDTC.2019.00015"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-01258-8_39"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218577"},{"key":"ref26","first-page":"4278","article-title":"Inception-v4, inception-resnet and the impact of residual connections on learning","author":"szegedy","year":"2017","journal-title":"Proc AAAI Conf Artif Intell"},{"key":"ref25","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2019.2956591"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.1109\/TDSC.2018.2874243"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2016.2518130"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1145\/1723112.1723154"},{"key":"ref53","article-title":"Enhancing fault tolerance of neural networks for security-critical applications","author":"alam","year":"2019","journal-title":"arXiv 1902 04560"},{"article-title":"Defensive quantization: When efficiency meets robustness","year":"0","author":"lin","key":"ref52"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1145\/2976749.2978392"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00175"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/SP40000.2020.00057"},{"key":"ref12","first-page":"3896","article-title":"Adversarial camera stickers: A physical camera-based attack on deep learning systems","volume":"97","author":"li","year":"2019","journal-title":"Proc 36th Int Conf Mach Learn (ICML)"},{"key":"ref13","first-page":"1989","article-title":"Seeing isn&#x2019;t believing: Towards more robust adversarial attack against real world object detectors","author":"zhao","year":"2019","journal-title":"Proc ACM SIGSAC Conf Comput Commun Secur"},{"key":"ref14","first-page":"284","article-title":"Synthesizing robust adversarial examples","author":"athalye","year":"2018","journal-title":"Proc 35th Int Conf Mach Learn (ICML)"},{"key":"ref15","first-page":"1","article-title":"Physical adversarial examples for object detectors","author":"eykholt","year":"2018","journal-title":"Proc 10th USENIX Workshop Offensive Technol (WOOT)"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1145\/3243734.3278519"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/ICCAD.2017.8203770"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3316781.3317825"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS.2019.8702493"},{"article-title":"Intriguing properties of neural networks","year":"0","author":"szegedy","key":"ref4"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TNNLS.2018.2808319"},{"article-title":"Adversarial machine learning at scale","year":"0","author":"kurakin","key":"ref6"},{"article-title":"Explaining and harnessing adversarial examples","year":"0","author":"goodfellow","key":"ref5"},{"key":"ref8","first-page":"10","article-title":"EAD: Elastic-net attacks to deep neural networks via adversarial examples","author":"chen","year":"2018","journal-title":"Proc 32nd AAAI Conf Artif Intell"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2017.49"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00099"},{"key":"ref9","article-title":"NO need to worry about adversarial examples in object detection in autonomous vehicles","author":"lu","year":"2017","journal-title":"arXiv 1707 03501"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1145\/3338508.3359572"},{"key":"ref45","doi-asserted-by":"publisher","DOI":"10.1109\/FDTC.2014.15"},{"journal-title":"Deep Neural Network Development Kit V3 0","year":"2019","key":"ref48"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10590-1_53"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1109\/AsianHOST47458.2019.9006701"},{"key":"ref41","first-page":"1445","article-title":"V0ltpwn: Attacking X86 processor integrity from software","author":"kenjar","year":"2020","journal-title":"Proc 29th USENIX Security Symp"},{"key":"ref44","first-page":"4:1","article-title":"Reverse engineering convolutional neural networks through side-channel information leaks","author":"hua","year":"2018","journal-title":"Proc 55th ACM\/ESDA\/IEEE Design Autom Conf (DAC)"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.1109\/DAC18072.2020.9218690"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/9151439\/09305299.pdf?arnumber=9305299","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,10]],"date-time":"2022-05-10T14:52:44Z","timestamp":1652194364000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9305299\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"references-count":55,"URL":"https:\/\/doi.org\/10.1109\/tifs.2020.3046858","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"type":"print","value":"1556-6013"},{"type":"electronic","value":"1556-6021"}],"subject":[],"published":{"date-parts":[[2021]]}}}