{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,2]],"date-time":"2026-07-02T16:26:27Z","timestamp":1783009587814,"version":"3.54.5"},"reference-count":41,"publisher":"Institute of Electrical and Electronics Engineers (IEEE)","license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100000646","name":"Japan Society for the Promotion of Science (JSPS) KAKENHI","doi-asserted-by":"publisher","award":["JP24K20774"],"award-info":[{"award-number":["JP24K20774"]}],"id":[{"id":"10.13039\/501100000646","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100006091","name":"Support Center for Advanced Telecommunications Technology Research","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100006091","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Access"],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/access.2025.3562563","type":"journal-article","created":{"date-parts":[[2025,4,21]],"date-time":"2025-04-21T17:39:37Z","timestamp":1745257177000},"page":"75194-75203","source":"Crossref","is-referenced-by-count":4,"title":["Privacy-Diffusion: Privacy-Preserving Stable Diffusion Without FHE and Differential Privacy"],"prefix":"10.1109","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0017-1657","authenticated-orcid":false,"given":"Po-Chu","family":"Hsu","sequence":"first","affiliation":[{"name":"Animechain.ai Inc., Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-3706-9765","authenticated-orcid":false,"given":"Ziying","family":"Yu","sequence":"additional","affiliation":[{"name":"Amazon, Irvine, CA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0009-4022-7350","authenticated-orcid":false,"given":"Shuhei","family":"Mise","sequence":"additional","affiliation":[{"name":"Animechain.ai Inc., Tokyo, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4182-8141","authenticated-orcid":false,"given":"Hideaki","family":"Miyaji","sequence":"additional","affiliation":[{"name":"Department of Information Science and Engineering, Ritsumeikan University, Kusatsu, Japan"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"263","reference":[{"key":"ref1","article-title":"SDXL: Improving latent diffusion models for high-resolution image synthesis","author":"Podell","year":"2023","journal-title":"arXiv:2307.01952"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.02155"},{"key":"ref3","first-page":"1","article-title":"Lora: Low-rank adaptation of large language models","volume-title":"Proc. ICLR","author":"Hu"},{"key":"ref4","first-page":"8821","article-title":"Zero-shot text-to-image generation","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Ramesh"},{"key":"ref5","volume-title":"Flux-black Forest Labs","year":"2024"},{"key":"ref6","volume-title":"Ideogram AI","year":"2024"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.48550\/arXiv.1810.04805"},{"key":"ref8","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Radford"},{"key":"ref9","article-title":"Efficient estimation of word representations in vector space","author":"Mikolov","year":"2013","journal-title":"arXiv:1301.3781"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-24574-4_28"},{"key":"ref11","volume-title":"Auto-encoding variational Bayes","author":"Kingma","year":"2022"},{"key":"ref12","article-title":"K-sparse autoencoders","author":"Makhzani","year":"2014","journal-title":"arXiv:1312.5663"},{"key":"ref13","first-page":"1","article-title":"Beta-VAE: Learning basic visual concepts with a constrained variational framework","volume-title":"Proc. Int. Conf. Learn. Represent.","author":"Higgins"},{"key":"ref14","first-page":"5253","article-title":"Extracting training data from diffusion models","volume-title":"Proc. 32nd USENIX Secur. Symp. (USENIX Secur. 23)","author":"Carlini"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2022.3176948"},{"key":"ref16","article-title":"Privacy-preserving diffusion model using homomorphic encryption","author":"Chen","year":"2024","journal-title":"arXiv:2403.05794"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1145\/2633600"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-70694-8_15"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00286"},{"key":"ref20","article-title":"Differentially private diffusion models","author":"Dockhorn","year":"2022","journal-title":"arXiv:2210.09929"},{"key":"ref21","volume-title":"Microsoft SEAL","year":"2019"},{"key":"ref22","article-title":"TenSEAL: A library for encrypted tensor operations using homomorphic encryption","author":"Benaissa","year":"2021","journal-title":"arXiv:2104.03152"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/ICCE63647.2025.10929778"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/3488932.3523253"},{"key":"ref25","first-page":"201","article-title":"CryptoNets: Applying neural networks to encrypted data with high throughput and accuracy","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Dowlin"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.58496\/BJIoT\/2023\/005"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/2022.findings-acl.277"},{"key":"ref28","volume-title":"Privacy-preserving tree-based inference with fully homomorphic encryption","author":"Frery","year":"2023"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1145\/3407023.3407045"},{"key":"ref30","first-page":"1814","article-title":"The PII problem: Privacy and a new concept of personally identifiable information","volume":"86","author":"Schwartz","year":"2011","journal-title":"NYUL Rev."},{"key":"ref31","doi-asserted-by":"crossref","first-page":"1","DOI":"10.70470\/SHIFRA\/2023\/001","article-title":"Privacy-preserving data mining techniques in big data: Balancing security and usability","author":"Abdulbaqi","year":"2023","journal-title":"SHIFRA"},{"key":"ref32","doi-asserted-by":"publisher","DOI":"10.1109\/SPW59333.2023.00013"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-44774-1_14"},{"key":"ref34","article-title":"Does fully homomorphic encryption need compute acceleration?","author":"de Castro","year":"2021","journal-title":"arXiv:2112.06396"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1109\/TC.2013.154"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2017.225"},{"key":"ref37","doi-asserted-by":"publisher","DOI":"10.1109\/HPCA51647.2021.00013"},{"key":"ref38","first-page":"2173","article-title":"AutoFHE: Automated adaption of CNNs for efficient evaluation over FHE","volume-title":"Proc. 33rd USENIX Secur. Symp. (USENIX Secur. 24)","author":"Ao"},{"key":"ref39","first-page":"4839","article-title":"DeepReDuce: ReLU reduction for fast private inference","volume-title":"Proc. Int. Conf. Mach. Learn.","author":"Jha"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.00478"},{"key":"ref41","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.01042"}],"container-title":["IEEE Access"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/6287639\/10820123\/10971394.pdf?arnumber=10971394","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,7]],"date-time":"2025-05-07T04:26:02Z","timestamp":1746591962000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/10971394\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":41,"URL":"https:\/\/doi.org\/10.1109\/access.2025.3562563","relation":{},"ISSN":["2169-3536"],"issn-type":[{"value":"2169-3536","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]}}}