mlsanityData to 7 Oct 2026

Copyright Protection and Accountability of Generative AI:Attack, Watermarking and Attribution

arXiv 2303.09272 ↗First posted 15 Mar 2023cs.LG cs.CR cs.MMcited by 15

On the map: LLM safety and security → Watermarking generated content and models

Abstract (arXiv)

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 the factors that affect their performance and future research directions. Our findings indicate that the current IPR protection methods for input images, model watermarking, and attribution networks are largely satisfactory for a wide range of GANs. We highlight that further attention must be directed towards protecting training sets, as the current approaches fail to provide robust IPR protection and provenance tracing on training sets.

Key facts. Cited by 15 papers in the map (data through 7 Oct 2026). Placed in Watermarking generated content and models, one of 12 directions in LLM safety and security. Builds on 17 of its 20 references that are in the map. First posted on arXiv 15 Mar 2023.

Builds on

17 of 20 references.

Closest ancestors · 2

Same direction, newest first

  1. 2021Copy, Right? A Testing Framework for Copyright Protection of Deep Learning Models10 Dec
  2. 2021CMUA-Watermark: A Cross-Model Universal Adversarial Watermark for Combating Deepfakes23 May

Other references · 15

  1. 2014Deep Learning Face Attributes in the Wildcited by 3,679
  2. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  3. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  4. 2019StarGAN v2: Diverse Image Synthesis for Multiple Domainscited by 1,095
  5. 2017StarGAN: Unified Generative Adversarial Networks for Multi-Domain Image-to-Image Translationcited by 1,036
  6. 2020Contrastive Learning for Unpaired Image-to-Image Translationcited by 637
  7. 2019MaskGAN: Towards Diverse and Interactive Facial Image Manipulationcited by 624
  8. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
  9. 2020Leveraging Frequency Analysis for Deep Fake Image Recognitioncited by 501
  10. 2020Artificial Fingerprinting for Generative Models: Rooting Deepfake Attribution in Training Datacited by 200
  11. 2021StyleSwin: Transformer-based GAN for High-resolution Image Generationcited by 152
  12. 2020Disrupting Deepfakes: Adversarial Attacks Against Conditional Image Translation Networks and Facial Manipulation Systemscited by 65
3 more
  1. 2022Deepfake Network Architecture Attributioncited by 47
  2. 2021Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attackcited by 45
  3. 2022Supervised GAN Watermarking for Intellectual Property Protectioncited by 39

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 5; 2024: 5; 2025: 4; 2026: 1.

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  1. 2023Towards Possibilities & Impossibilities of AI-generated Text Detection: A Surveycited by 28
  2. 2024Automatic Jailbreaking of the Text-to-Image Generative AI Systemscited by 22
  3. 2024GROOT: Generating Robust Watermark for Diffusion-Model-Based Audio Synthesiscited by 17
  4. 2023User Experience Design Professionals' Perceptions of Generative Artificial Intelligencecited by 16
  5. 2023Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyondcited by 14
  6. 2023Defenses in Adversarial Machine Learning: A Surveycited by 14
  7. 2024U Can't Gen This? A Survey of Intellectual Property Protection Methods for Data in Generative AIcited by 7
  8. 2025Un-Straightening Generative AI: How Queer Artists Surface and Challenge the Normativity of Generative AI Modelscited by 6
  9. 2023Survey on AI Ethics: A Socio-technical Perspectivecited by 4
  10. 2025The Theater Stage as Laboratory: Review of Real-Time Comedy LLM Systems for Live Performancecited by 4
  11. 2025AMCR: A Framework for Assessing and Mitigating Copyright Risks in Generative Modelscited by 3
  12. 2024Uncertain Boundaries: Multidisciplinary Approaches to Copyright Issues in Generative AIcited by 1
3 more
  1. 2024Psittacines of Innovation? Assessing the True Novelty of AI Creationscited by 0
  2. 2025Open Set Face Forgery Detection via Dual-Level Evidence Collectioncited by 0
  3. 2026Semantic Differentiation for Tackling Challenges in Watermarking Low-Entropy Constrained Generation Outputscited by 0