{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,15]],"date-time":"2026-07-15T06:06:48Z","timestamp":1784095608260,"version":"3.55.0"},"reference-count":44,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","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"}],"funder":[{"name":"National Intelligence and Security Discovery Research"},{"name":"Department of Defence, Australia","award":["NS220100007"],"award-info":[{"award-number":["NS220100007"]}]},{"name":"Australian Research Council Discovery Early Career Award"},{"DOI":"10.13039\/100015539","name":"Australian Government","doi-asserted-by":"publisher","award":["DE230101058"],"award-info":[{"award-number":["DE230101058"]}],"id":[{"id":"10.13039\/100015539","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Australian Research Council Future Fellowship Award"},{"DOI":"10.13039\/100015539","name":"Australian Government","doi-asserted-by":"publisher","award":["FT210100268"],"award-info":[{"award-number":["FT210100268"]}],"id":[{"id":"10.13039\/100015539","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2024]]},"DOI":"10.1109\/tifs.2024.3386058","type":"journal-article","created":{"date-parts":[[2024,4,8]],"date-time":"2024-04-08T20:48:26Z","timestamp":1712609306000},"page":"4865-4880","source":"Crossref","is-referenced-by-count":33,"title":["BAGM: A Backdoor Attack for Manipulating Text-to-Image Generative Models"],"prefix":"10.1109","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3951-1188","authenticated-orcid":false,"given":"Jordan","family":"Vice","sequence":"first","affiliation":[{"name":"Department of Computer Science and Software Engineering, The University of Western Australia, Perth, WA, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3406-673X","authenticated-orcid":false,"given":"Naveed","family":"Akhtar","sequence":"additional","affiliation":[{"name":"School of Computing and Information Systems, The University of Melbourne, Melbourne, VIC, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5005-0191","authenticated-orcid":false,"given":"Richard","family":"Hartley","sequence":"additional","affiliation":[{"name":"Department of Systems Engineering, RSISE, The Australian National University, Canberra, ACT, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5206-3842","authenticated-orcid":false,"given":"Ajmal","family":"Mian","sequence":"additional","affiliation":[{"name":"Department of Computer Science and Software Engineering, The University of Western Australia, Perth, WA, Australia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1145\/3422622"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/tpami.2023.3261988"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/access.2019.2905015"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1109\/jas.2017.7510583"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/tii.2022.3155656"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.3390\/electronics8030292"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3626235"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3127960"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2020.07.133"},{"key":"ref10","article-title":"A survey of neural trojan attacks and defenses in deep learning","author":"Wang","year":"2022","journal-title":"arXiv:2202.07183"},{"key":"ref11","volume-title":"Stable Diffusion Launch Announcement","year":"2023"},{"key":"ref12","volume-title":"Kandinsky2.2, HuggingFace","year":"2023"},{"key":"ref13","article-title":"Hierarchical text-conditional image generation with CLIP latents","author":"Ramesh","year":"2022","journal-title":"arXiv:2204.06125"},{"key":"ref14","volume-title":"DeepFloyd-IF-I-M-v1.0","year":"2023"},{"key":"ref15","first-page":"36479","article-title":"Photorealistic text-to-image diffusion models with deep language understanding","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Saharia"},{"key":"ref16","first-page":"8780","article-title":"Diffusion models beat GANs on image synthesis","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"34","author":"Dhariwal"},{"key":"ref17","first-page":"2256","article-title":"Deep unsupervised learning using nonequilibrium thermodynamics","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Sohl-Dickstein"},{"key":"ref18","first-page":"6840","article-title":"Denoising diffusion probabilistic models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"33","author":"Ho"},{"key":"ref19","first-page":"11895","article-title":"Generative modeling by estimating gradients of the data distribution","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"32","author":"Song"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"},{"key":"ref21","article-title":"SEGA: Instructing text-to-image models using semantic guidance","author":"Brack","year":"2023","journal-title":"arXiv:2301.12247"},{"key":"ref22","first-page":"1","article-title":"Score-based generative modeling through stochastic differential equations","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Song"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref24","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. 38th Int. Conf. Mach. Learn.","volume":"139","author":"Radford"},{"key":"ref25","first-page":"25278","article-title":"LAION-5B: An open large-scale dataset for training next generation image-text models","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"35","author":"Schuhmann"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/isqed48828.2020.9137011"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2021.3108407"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/access.2021.3101289"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/globalsip.2018.8646335"},{"key":"ref30","doi-asserted-by":"publisher","DOI":"10.1145\/3319535.3354209"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1007\/s11633-022-1377-5"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1145\/3581783.3612108"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00391"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.01972"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00393"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00392"},{"key":"ref37","volume-title":"Supercharging Search With Generative AI","author":"Reid","year":"2023"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02155"},{"issue":"1","key":"ref39","first-page":"5485","article-title":"Exploring the limits of transfer learning with a unified text-to-text transformer","volume":"21","author":"Raffel","year":"2020","journal-title":"J. Mach. Learn. Res."},{"key":"ref40","first-page":"6627","article-title":"Gans trained by a two time-scale update rule converge to a local Nash equilibrium","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","volume":"30","author":"Heusel"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/tifs.2022.3226905"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-10602-1_48"},{"key":"ref43","first-page":"12888","article-title":"BLIP: Bootstrapping language-image pre-training for unified vision-language understanding and generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Li"},{"key":"ref44","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00423"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/10206\/10319981\/10494544.pdf?arnumber=10494544","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,5,9]],"date-time":"2024-05-09T17:27:48Z","timestamp":1715275668000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10494544\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"references-count":44,"URL":"https:\/\/doi.org\/10.1109\/tifs.2024.3386058","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"value":"1556-6013","type":"print"},{"value":"1556-6021","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]}}}