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Free Fine-tuning: A Plug-and-Play Watermarking Scheme for Deep Neural Networks. (arXiv:2210.07809v1 [cs.CR])
Oct. 17, 2022, 1:20 a.m. | Run Wang, Jixing Ren, Boheng Li, Tianyi She, Chehao Lin, Liming Fang, Jing Chen, Chao Shen, Lina Wang
cs.CR updates on arXiv.org arxiv.org
Watermarking has been widely adopted for protecting the intellectual property
(IP) of Deep Neural Networks (DNN) to defend the unauthorized distribution.
Unfortunately, the popular data-poisoning DNN watermarking scheme relies on
target model fine-tuning to embed watermarks, which limits its practical
applications in tackling real-world tasks. Specifically, the learning of
watermarks via tedious model fine-tuning on a poisoned dataset
(carefully-crafted sample-label pairs) is not efficient in tackling the tasks
on challenging datasets and production-level DNN model protection. To address
the aforementioned …
More from arxiv.org / cs.CR updates on arXiv.org
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