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Multimedia Comput. Commun. Appl."],"published-print":{"date-parts":[[2025,2,28]]},"abstract":"<jats:p>Zero-watermarking is an emerging distortion-free copyright protection method for volumetric medical images. However, achieving both robustness against various malicious attacks and distinguishability between individual images remains challenging. In this article, we propose a novel attack-defending contrastive learning zero-watermarking (ADCL-ZW) scheme to tackle the above challenge using deep learning-based representations. In our approach, we design an attack-defending data enrichment mechanism to enhance the watermarking robustness by generating a large number of image samples under various watermarking attacks. Subsequently, features for both watermarking distinguishability and robustness are enhanced through application of a contrastive loss. In particular, we implement a dual-stream Siamese network architecture to effectively handle both signal attacks and geometric attacks in order to enhance the watermarking performance. Experimental results demonstrate that ADCL-ZW achieves stronger watermarking robustness and a better tradeoff between watermarking robustness and distinguishability compared with state-of-the art zero-watermarking methods. One of the highlighted metrics is that the false-negative rate of ADCL-ZW achieves 0.01 when a fixed false-positive rate is set to 1%, which is more than 13.3 times better than the benchmark methods.<\/jats:p>","DOI":"10.1145\/3702230","type":"journal-article","created":{"date-parts":[[2024,11,5]],"date-time":"2024-11-05T16:38:18Z","timestamp":1730824698000},"page":"1-23","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":5,"title":["Attack-Defending Contrastive Learning for Volumetric Medical Image Zero-Watermarking"],"prefix":"10.1145","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2718-659X","authenticated-orcid":false,"given":"Xiyao","family":"Liu","sequence":"first","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2782-0757","authenticated-orcid":false,"given":"Cundian","family":"Yang","sequence":"additional","affiliation":[{"name":"Shenzhen Graduate School, Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3524-8877","authenticated-orcid":false,"given":"Jianbiao","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9365-7420","authenticated-orcid":false,"given":"Hui","family":"Fang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Loughborough University, Loughborough, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1292-7674","authenticated-orcid":false,"given":"Gerald","family":"Schaefer","sequence":"additional","affiliation":[{"name":"Department of Computer Science, Loughborough University, Loughborough, U.K."}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5418-0455","authenticated-orcid":false,"given":"Jian","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Central South University, Changsha, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2524-6800","authenticated-orcid":false,"given":"Yuesheng","family":"Zhu","sequence":"additional","affiliation":[{"name":"Shenzhen Graduate School, Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9981-2970","authenticated-orcid":false,"given":"Shichao","family":"Zhang","sequence":"additional","affiliation":[{"name":"Key Lab for Guangxi MIMS, College of Computer Science, Guangxi Normal University, Guilin, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,12,26]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2016.11.044"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1007\/s11042-020-09981-5"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV48922.2021.00950"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116193"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1504\/IJHPCN.2019.097508"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.00975"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1145\/3325193"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.bspc.2021.103007"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvcir.2020.102804"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.3390\/s22155612"},{"key":"e_1_3_1_12_2","first-page":"1","volume-title":"ICML Deep Learning Workshop","author":"Koch Gregory","year":"2015","unstructured":"Gregory Koch, Richard Zemel, and Ruslan Salakhutdinov. 2015. 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