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For example, artists become concerned that GDMs could effortlessly replicate their unique artworks without permission. In response to these challenges, we introduce a novel watermark scheme, Diffusion Shield, against GDMs. It protects images from infringement by encoding the ownership message into an imperceptible watermark and injecting it into images. This watermark can be easily learned by GDMs and will be reproduced in generated images. By detecting the watermark in generated images, the infringement can be exposed with evidence. Benefiting from the uniformity of the watermarks and the joint optimization method, Diffusion Shield ensures low distortion of the original image, high watermark detection performance, and lengthy encoded messages. We conduct rigorous and comprehensive experiments to show its effectiveness in defending against infringement by GDMs and its superiority over traditional watermark methods.<\/jats:p>","DOI":"10.1145\/3715073.3715079","type":"journal-article","created":{"date-parts":[[2025,1,29]],"date-time":"2025-01-29T23:19:36Z","timestamp":1738192776000},"page":"60-75","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":19,"title":["DiffusionShield: A Watermark for Data Copyright Protection against Generative Diffusion Models"],"prefix":"10.1145","volume":"26","author":[{"given":"Yingqian","family":"Cui","sequence":"first","affiliation":[{"name":"Michigan State University"}]},{"given":"Jie","family":"Ren","sequence":"additional","affiliation":[{"name":"Michigan State University"}]},{"given":"Han","family":"Xu","sequence":"additional","affiliation":[{"name":"The University of Arizona"}]},{"given":"Pengfei","family":"He","sequence":"additional","affiliation":[{"name":"Michigan State University"}]},{"given":"Hui","family":"Liu","sequence":"additional","affiliation":[{"name":"Michigan State University"}]},{"given":"Lichao","family":"Sun","sequence":"additional","affiliation":[{"name":"Lehigh University"}]},{"given":"Yue","family":"Xing","sequence":"additional","affiliation":[{"name":"Michigan State University"}]},{"given":"Jiliang","family":"Tang","sequence":"additional","affiliation":[{"name":"Michigan State University"}]}],"member":"320","published-online":{"date-parts":[[2025,1,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/FOCS52979.2021.00098"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1162\/tacl_a_00106"},{"key":"e_1_2_1_3_1","volume-title":"International conference on learning representations","author":"Ba Jimmy","year":"2019","unstructured":"Jimmy Ba, Murat Erdogdu, Taiji Suzuki, Denny Wu, and Tianzong Zhang. 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