mlsanityData to 14 Oct 2026

Challenges and Remedies to Privacy and Security in AIGC: Exploring the Potential of Privacy Computing, Blockchain, and Beyond

arXiv 2306.00419 ↗First posted 1 Jun 2023cs.CR cs.AIcited by 14

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Abstract (arXiv)

Artificial Intelligence Generated Content (AIGC) is one of the latest achievements in AI development. The content generated by related applications, such as text, images and audio, has sparked a heated discussion. Various derived AIGC applications are also gradually entering all walks of life, bringing unimaginable impact to people's daily lives. However, the rapid development of such generative tools has also raised concerns about privacy and security issues, and even copyright issues in AIGC. We note that advanced technologies such as blockchain and privacy computing can be combined with AIGC tools, but no work has yet been done to investigate their relevance and prospect in a systematic and detailed way. Therefore it is necessary to investigate how they can be used to protect the privacy and security of data in AIGC by fully exploring the aforementioned technologies. In this paper, we first systematically review the concept, classification and underlying technologies of AIGC. Then, we discuss the privacy and security challenges faced by AIGC from multiple perspectives and purposefully list the countermeasures that currently exist. We hope our survey will help researchers and industry to build a more secure and robust AIGC system.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 147 of its 246 references that are in the map. First posted on arXiv 1 Jun 2023.

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147 of 246 references.

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Citing papers per year: 2023: 4; 2024: 9; 2025: 1.

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  1. 2023Decentralized Federated Learning: A Survey and Perspectivecited by 86
  2. 2024Prompt-Agnostic Adversarial Perturbation for Customized Diffusion Modelscited by 14
  3. 2024A Survey of Defenses Against AI-Generated Visual Media: Detection,Disruption, and Authenticationcited by 13
  4. 2024Replication in Visual Diffusion Models: A Survey and Outlookcited by 11
  5. 2024U Can't Gen This? A Survey of Intellectual Property Protection Methods for Data in Generative AIcited by 7
  6. 2023A Survey of Generative AI for Intelligent Transportation Systems: Road Transportation Perspectivecited by 6
  7. 2024AIGCs Confuse AI Too: Investigating and Explaining Synthetic Image-induced Hallucinations in Large Vision-Language Modelscited by 6
  8. 2023Innovative Digital Storytelling with AIGC: Exploration and Discussion of Recent Advancescited by 2
  9. 2024Lazy Layers to Make Fine-Tuned Diffusion Models More Traceablecited by 2
  10. 2024MemHunter: Automated and Verifiable Memorization Detection at Dataset-scale in LLMscited by 2
  11. 2024Copyleft for Alleviating AIGC Copyright Dilemma: What-if Analysis, Public Perception and Implicationscited by 1
  12. 2025Origin Identification for Text-Guided Image-to-Image Diffusion Modelscited by 1
2 more
  1. 2023RAEDiff: Denoising Diffusion Probabilistic Models Based Reversible Adversarial Examples Self-Generation and Self-Recoverycited by 0
  2. 2024RO-SVD: A Reconfigurable Hardware Copyright Protection Framework for AIGC Applicationscited by 0