Copyright Protection and Accountability of Generative AI:Attack, Watermarking and Attribution. (arXiv:2303.09272v1 [cs.LG])

Generative AI (e.g., Generative Adversarial Networks - GANs) has become
increasingly popular in recent years. However, Generative AI introduces
significant concerns regarding the protection of Intellectual Property Rights
(IPR) (resp. model accountability) pertaining to images (resp. toxic images)
and models (resp. poisoned models) generated. In this paper, we propose an
evaluation framework to provide a comprehensive overview of the current state
of the copyright protection measures for GANs, evaluate their performance
across a diverse range of GAN architectures, and identify …

accountability adversarial attack attribution copyright current evaluation framework gans generated generative generative adversarial networks generative ai images intellectual property networks popular protection rights state toxic watermarking