为生成图像设计抗删除与伪造攻击的动态水印方案
Towards Robust Content Watermarking Against Removal and Forgery Attacks
- 根据用户提示语义动态控制水印注入时机和模式
- 提出双向检测机制，显著提升水印鲁棒性
- 适合需要版权保护的AI内容创作者使用
生成内容引发了关于版权保护、图像来源追溯和信用归属的严重关切。水印技术是解决这些问题的潜在方案。近年来，针对文本到图像扩散模型的内容水印因其有效的检测能力和鲁棒性而受到广泛关注。然而，现有水印技术易受删除攻击和伪造攻击等对抗性攻击的影响。本文提出一种新型水印范式——实例特定双向检测水印（ISTS），以抵御删除与伪造攻击。具体而言，我们设计了一种策略，根据用户提示的语义动态控制水印注入时间及模式；同时，提出一种新的双向检测方法，增强水印检测的鲁棒性。实验表明，该水印在抵抗删除和伪造攻击方面表现更优。
原文摘要 · Abstract (English)
Generated contents have raised serious concerns about copyright protection, image provenance, and credit attribution. A potential solution for these problems is watermarking. Recently, content watermarking for text-to-image diffusion models has been studied extensively for its effective detection utility and robustness. However, these watermarking techniques are vulnerable to potential adversarial attacks, such as removal attacks and forgery attacks. In this paper, we build a novel watermarking paradigm called Instance-Specific watermarking with Two-Sided detection (ISTS) to resist removal and forgery attacks. Specifically, we introduce a strategy that dynamically controls the injection time and watermarking patterns based on the semantics of users' prompts. Furthermore, we propose a new two-sided detection approach to enhance robustness in watermark detection. Experiments have demonstrated the superiority of our watermarking against removal and forgery attacks.
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