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English(EN) CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint

新研究探索用于抵抗攻击的扩散模型鲁棒水印技术

新研究探讨了生成式AI模型中水印的漏洞和潜在防御措施。一项研究表明,多步重写攻击会显著降低扩散语言模型中水印的检测率,在几次编辑后使其失效。另一篇论文从理论上分析了水印在对抗符号损坏方面的鲁棒性极限,表明在检测变得不可靠之前,超过一半的编码比特可以被修改。此外,研究还为扩散模型引入了新颖的水印方法,包括一种使用压缩感知的抗伪造方法以及一个用于评估安全性、鲁棒性和保真度的理论基础框架。 AI

影响 新研究突显了当前AI水印技术存在的重大漏洞,表明需要更鲁棒且有理论基础的方法来确保内容真实性和知识产权保护。

排序理由 该集群包含多篇学术论文,提出了关于生成模型水印技术的新研究。

在 arXiv cs.CV 阅读 →

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新研究探索用于抵抗攻击的扩散模型鲁棒水印技术

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报道来源 [7]

  1. arXiv cs.CL TIER_1 English(EN) · Mohd Ruhul Ameen, Akif Islam, Nadim Mahmud, Md. Ekramul Hamid ·

    Chainwash:对扩散语言模型水印的多步重写攻击

    arXiv:2605.05503v1 Announce Type: new Abstract: Statistical watermarking is a common approach for verifying whether text was written by a language model. Most existing schemes assume autoregressive generation, where tokens are produced left to right and contextual hashing is well…

  2. Hugging Face Daily Papers TIER_1 English(EN) ·

    Chainwash:对扩散语言模型水印的多步重写攻击

    Statistical watermarking is a common approach for verifying whether text was written by a language model. Most existing schemes assume autoregressive generation, where tokens are produced left to right and contextual hashing is well defined. Diffusion language models generate tex…

  3. arXiv cs.AI TIER_1 English(EN) · Danilo Francati, Yevin Nikhel Goonatilake, Shubham Pawar, Daniele Venturi, Giuseppe Ateniese ·

    生成模型鲁棒水印的编码限制

    arXiv:2509.10577v3 Announce Type: replace-cross Abstract: We study a basic question about cryptographic watermarking for generative models: how reliable can a watermark remain when an adversary is allowed to corrupt the encoded signal? To address this question, we introduce a min…

  4. arXiv cs.CV TIER_1 English(EN) · Enoal Gesny, Eva Giboulot ·

    从第一性原理出发,为扩散模型设计基于种子的安全多比特水印

    arXiv:2605.06153v1 Announce Type: cross Abstract: The rapid emergence of generative image models has led to the development of specialized watermarking techniques, particularly in-generation methods such as seed-based embedding. However, current evaluations in this area remain la…

  5. arXiv cs.CV TIER_1 English(EN) · Enoal Gesny, Eva Giboulot, Teddy Furon, Vivien Chappelier ·

    Guidance Watermarking for Diffusion Models

    arXiv:2509.22126v2 Announce Type: replace-cross Abstract: This paper introduces a novel watermarking method for diffusion models. It is based on guiding the diffusion process using the gradient computed from any off-the-shelf watermark decoder. The gradient computation encompasse…

  6. arXiv cs.CV TIER_1 English(EN) · Eva Giboulot ·

    从第一性原理出发,为扩散模型设计基于种子的安全多比特水印

    The rapid emergence of generative image models has led to the development of specialized watermarking techniques, particularly in-generation methods such as seed-based embedding. However, current evaluations in this area remain largely empirical, making them heavily reliant on th…

  7. arXiv cs.CV TIER_1 English(EN) · Jiewei Lai, Lan Zhang, Chen Tang, Pengcheng Sun, Zhaopeng Zhang, Yunhao Wang, Hui Jin ·

    CSGuard:通过压缩感知约束实现抗伪造的扩散模型水印

    arXiv:2605.01479v1 Announce Type: new Abstract: Latent-based diffusion model watermarking embeds watermarks into generated images' latent space to enable content attribution, offering a training-free solution for intellectual property protection and digital forensics. However, th…