{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,17]],"date-time":"2025-09-17T22:42:28Z","timestamp":1758148948075,"version":"3.44.0"},"reference-count":80,"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:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["62372236","62402223"],"award-info":[{"award-number":["62372236","62402223"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Foundation of the Key Laboratory of Cyberspace Security, Ministry of Education","award":["KLCS20240204"],"award-info":[{"award-number":["KLCS20240204"]}]},{"name":"Postgraduate Research and Practice Innovation Program of Jiangsu Province","award":["KYCX25_0813"],"award-info":[{"award-number":["KYCX25_0813"]}]},{"DOI":"10.13039\/501100013088","name":"Qing Lan Project of Jiangsu Province","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100013088","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IEEE Trans.Inform.Forensic Secur."],"published-print":{"date-parts":[[2025]]},"DOI":"10.1109\/tifs.2025.3607234","type":"journal-article","created":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T17:43:39Z","timestamp":1757353419000},"page":"9523-9538","source":"Crossref","is-referenced-by-count":0,"title":["Division and Union: Latent Model Watermarking"],"prefix":"10.1109","volume":"20","author":[{"given":"Zhiyang","family":"Dai","sequence":"first","affiliation":[{"name":"School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6029-5064","authenticated-orcid":false,"given":"Yansong","family":"Gao","sequence":"additional","affiliation":[{"name":"The University of Western Australia, Perth, WA, Australia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5903-557X","authenticated-orcid":false,"given":"Boyu","family":"Kuang","sequence":"additional","affiliation":[{"name":"School of Cyber Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7852-6051","authenticated-orcid":false,"given":"Yifeng","family":"Zheng","sequence":"additional","affiliation":[{"name":"Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5206-3842","authenticated-orcid":false,"given":"Ajmal","family":"Mian","sequence":"additional","affiliation":[{"name":"The University of Western Australia, Perth, WA, Australia"}]},{"given":"Ruimin","family":"Wang","sequence":"additional","affiliation":[{"name":"Information Engineering University, Zhengzhou, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1632-5737","authenticated-orcid":false,"given":"Anmin","family":"Fu","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing, China"}]}],"member":"263","reference":[{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263-019-01247-4"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.220"},{"key":"ref3","article-title":"BERT: Pre-training of deep bidirectional transformers for language understanding","author":"Devlin","year":"2018","journal-title":"arXiv:1810.04805"},{"article-title":"Improving language understanding by generative pre-training","year":"2018","author":"Radford","key":"ref4"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1561\/116.00000050"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-63076-8_16"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1145\/3451471.3451485"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.312"},{"key":"ref9","article-title":"The cost of training NLP models: A concise overview","author":"Sharir","year":"2020","journal-title":"arXiv:2004.08900"},{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/SP46214.2022.9833747"},{"key":"ref11","article-title":"Stealing neural networks via timing side channels","author":"Duddu","year":"2018","journal-title":"arXiv:1812.11720"},{"key":"ref12","doi-asserted-by":"publisher","DOI":"10.1109\/TCAD.2022.3197499"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1145\/3323873.3325042"},{"key":"ref14","first-page":"311","article-title":"DeepSigns: A generic watermarking framework for IP protection of deep learning models","volume":"2018","author":"Rouhani","year":"2018","journal-title":"IACR Cryptol. ePrint Arch."},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1145\/3078971.3078974"},{"key":"ref16","article-title":"HufuNet: Embedding the left piece as watermark and keeping the right piece for ownership verification in deep neural networks","author":"Lv","year":"2021","journal-title":"arXiv:2103.13628"},{"key":"ref17","first-page":"1937","article-title":"Entangled watermarks as a defense against model extraction","volume-title":"Proc. USENIX Secur. Symp.","author":"Jia"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359801"},{"key":"ref19","doi-asserted-by":"publisher","DOI":"10.1145\/3196494.3196550"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1145\/3321705.3329808"},{"key":"ref21","first-page":"1615","article-title":"Turning your weakness into a strength: Watermarking deep neural networks by backdooring","volume-title":"Proc. 27th USENIX Conf. Security Symp.","author":"Adi"},{"article-title":"Deep neural network fingerprinting by conferrable adversarial examples","volume-title":"Proc. ICLR","author":"Lukas","key":"ref22"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1145\/3433210.3437526"},{"key":"ref24","article-title":"Backdoor attacks and countermeasures on deep learning: A comprehensive review","author":"Gao","year":"2020","journal-title":"arXiv:2007.10760"},{"key":"ref25","article-title":"Deep intellectual property protection: A survey","author":"Sun","year":"2023","journal-title":"arXiv:2304.14613"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2023.3312973"},{"key":"ref27","doi-asserted-by":"publisher","DOI":"10.1145\/3359789.3359790"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/SP.2019.00031"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1109\/SP40001.2021.00034"},{"article-title":"DeepEclipse: How to break white-box DNN-watermarking schemes","volume-title":"Proc. USENIX Secur.","author":"Pegoraro","key":"ref30"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/SP46214.2022.9833688"},{"article-title":"Domain watermark: Effective and harmless dataset copyright protection is closed at hand","volume-title":"Proc. Adv. Neural Inf. Process. Syst.","author":"Guo","key":"ref32"},{"key":"ref33","doi-asserted-by":"publisher","DOI":"10.1145\/3572777"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1145\/3297858.3304051"},{"key":"ref35","first-page":"487","article-title":"DeepAttest: An end-to-end attestation framework for deep neural networks","volume-title":"Proc. 46th Int. Symp. Comput. Architect.","author":"Chen"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-55393-7_33"},{"key":"ref37","first-page":"8326","article-title":"Radioactive data: Tracing through training","volume-title":"Proc. Int. Conf. Mach. Learning","author":"Sablayrolles"},{"key":"ref38","doi-asserted-by":"publisher","DOI":"10.1016\/j.ins.2021.06.073"},{"key":"ref39","first-page":"6978","article-title":"Watermarking deep neural networks with greedy residuals","volume-title":"Proc. ICML","author":"Liu"},{"key":"ref40","doi-asserted-by":"publisher","DOI":"10.1145\/3442381.3450000"},{"key":"ref41","first-page":"1780","article-title":"You are caught stealing my winning lottery ticket! Making a lottery ticket claim its ownership","volume-title":"Proc. NeurIPS","author":"Chen"},{"key":"ref42","doi-asserted-by":"publisher","DOI":"10.1145\/3433210.3453079"},{"key":"ref43","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/500"},{"key":"ref44","article-title":"Harmless backdoor-based client-side watermarking in federated learning","author":"Luo","year":"2024","journal-title":"arXiv:2410.21179"},{"key":"ref45","article-title":"Intellectual property protection for deep learning model and dataset intelligence","author":"Jiang","year":"2024","journal-title":"arXiv:2411.05051"},{"key":"ref46","doi-asserted-by":"publisher","DOI":"10.1109\/SP40001.2021.00106"},{"key":"ref47","doi-asserted-by":"publisher","DOI":"10.1109\/TIFS.2022.3198267"},{"key":"ref48","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3548247"},{"key":"ref49","doi-asserted-by":"publisher","DOI":"10.1109\/ISCAS51556.2021.9401119"},{"key":"ref50","doi-asserted-by":"publisher","DOI":"10.1145\/3534678.3539257"},{"key":"ref51","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2022\/109"},{"article-title":"Are you stealing my model? Sample correlation for fingerprinting deep neural networks","volume-title":"Proc. NeurIPS","author":"Guan","key":"ref52"},{"key":"ref53","doi-asserted-by":"publisher","DOI":"10.1109\/SP46215.2023.10179380"},{"key":"ref54","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v36i2.20036"},{"key":"ref55","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413729"},{"key":"ref56","doi-asserted-by":"publisher","DOI":"10.1145\/3437880.3460402"},{"key":"ref57","doi-asserted-by":"publisher","DOI":"10.1109\/ICTAI52525.2021.00031"},{"article-title":"Learning multiple layers of features from tiny images","year":"2009","author":"Krizhevsky","key":"ref58"},{"volume-title":"Imagenette","year":"2019","key":"ref59"},{"issue":"7","key":"ref60","first-page":"3","article-title":"Tiny ImageNet visual recognition challenge","volume":"7","author":"Le","year":"2015"},{"key":"ref61","article-title":"Products-10K: A large-scale product recognition dataset","author":"Bai","year":"2020","journal-title":"arXiv:2008.10545"},{"volume-title":"Famous Brand Logos","year":"2021","key":"ref62"},{"key":"ref63","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"article-title":"Very deep convolutional networks for large-scale image recognition","volume-title":"Proc. ICLR","author":"Simonyan","key":"ref64"},{"key":"ref65","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2009.5206848"},{"key":"ref66","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2025.3530988"},{"issue":"86","key":"ref67","first-page":"2579","article-title":"Visualizing data using t-SNE","volume":"9","author":"Maaten","year":"2008","journal-title":"J. Mach. Learn. Res."},{"key":"ref68","first-page":"8748","article-title":"Learning transferable visual models from natural language supervision","volume-title":"Proc. Int. Conf. Mach. Learn.","volume":"139","author":"Radford"},{"volume-title":"DBPedia Classes","year":"2019","key":"ref69"},{"volume-title":"AG News Classification Dataset","year":"2020","key":"ref70"},{"key":"ref71","first-page":"1813","article-title":"REMARK-LLM: A robust and efficient watermarking framework for generative large language models","volume-title":"Proc. USENIX Secur.","author":"Zhang"},{"key":"ref72","article-title":"Token-specific watermarking with enhanced detectability and semantic coherence for large language models","author":"Huo","year":"2024","journal-title":"arXiv:2402.18059"},{"article-title":"Optimizing watermarks for large language models","volume-title":"Proc. ICML","author":"Wouters","key":"ref73"},{"key":"ref74","doi-asserted-by":"publisher","DOI":"10.1145\/3433210.3453090"},{"key":"ref75","doi-asserted-by":"publisher","DOI":"10.1145\/3579856.3590336"},{"key":"ref76","doi-asserted-by":"publisher","DOI":"10.1109\/SP46214.2022.9833607"},{"key":"ref77","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v38i7.28619"},{"key":"ref78","doi-asserted-by":"publisher","DOI":"10.1109\/SP54263.2024.00250"},{"key":"ref79","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2024.24374"},{"key":"ref80","doi-asserted-by":"publisher","DOI":"10.14722\/ndss.2025.230338"}],"container-title":["IEEE Transactions on Information Forensics and Security"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx8\/10206\/10810755\/11153578.pdf?arnumber=11153578","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,16]],"date-time":"2025-09-16T17:33:17Z","timestamp":1758043997000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/11153578\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":80,"URL":"https:\/\/doi.org\/10.1109\/tifs.2025.3607234","relation":{},"ISSN":["1556-6013","1556-6021"],"issn-type":[{"type":"print","value":"1556-6013"},{"type":"electronic","value":"1556-6021"}],"subject":[],"published":{"date-parts":[[2025]]}}}