Text-to-image diffusion models have emerged as powerful tools for generating high-quality images from textual descriptions. However, their increasing popularity has raised significant copyright concerns, as these models can be misused to reproduce copyrighted content without authorization. In response, recent studies have proposed various copyright protection methods, including adversarial perturbation, concept erasure, and watermarking techniques. However, their effectiveness and robustness against advanced attacks remain largely unexplored. Moreover, the lack of unified evaluation frameworks has hindered systematic comparison and fair assessment of different approaches. To bridge this gap, we systematize existing copyright protection methods and attacks, providing a unified taxonomy of their design spaces. We then develop CopyrightMeter, a unified evaluation framework that incorporates 17 state-of-the-art protections and 16 representative attacks. Leveraging CopyrightMeter, we comprehensively evaluate protection methods across multiple dimensions, thereby uncovering how different design choices impact fidelity, efficacy, and resilience under attacks. Our analysis reveals several key findings: (i) most protections (16/17) are not resilient against attacks; (ii) the "best" protection varies depending on the target priority; (iii) more advanced attacks significantly promote the upgrading of protections. These insights provide concrete guidance for developing more robust protection methods, while its unified evaluation protocol establishes a standard benchmark for future copyright protection research in text-to-image generation.

翻译：文本到图像扩散模型已成为根据文本描述生成高质量图像的强大工具。然而，其日益增长的应用引发了严重的版权担忧，因为这些模型可能被滥用于未经授权复制受版权保护的内容。为此，近期研究提出了多种版权保护方法，包括对抗性扰动、概念擦除和水印技术等。然而，这些方法在应对高级攻击时的有效性和鲁棒性在很大程度上仍未得到充分探索。此外，缺乏统一的评估框架阻碍了对不同方法的系统比较和公正评估。为弥补这一差距，本文系统梳理了现有版权保护方法与攻击手段，对其设计空间进行了统一分类。在此基础上，我们开发了CopyrightMeter——一个集成了17种前沿保护方法和16种代表性攻击的统一评估框架。借助CopyrightMeter，我们从多个维度对保护方法进行全面评估，从而揭示不同设计选择如何影响模型在攻击下的保真度、效能和抗性。我们的分析得出若干关键发现：(i) 大多数保护方法（16/17）无法有效抵御攻击；(ii) "最佳"保护方案因目标优先级而异；(iii) 更先进的攻击能显著推动保护技术的升级。这些发现为开发更鲁棒的保护方法提供了具体指导，同时其统一评估协议为未来文本到图像生成领域的版权保护研究建立了标准基准。