Secure Seed-Based Multi-bit Watermarking for Diffusion Models from First Principles
Enoal Gesny, Eva Giboulot

TL;DR
This paper introduces a theoretical framework for evaluating seed-based watermarking in diffusion models, enabling rigorous security, robustness, and fidelity analysis independent of specific generative architectures.
Contribution
It proposes a formal evaluation method and a new watermarking technique, SSB, that achieves any desired trade-off on the security-robustness-fidelity surface.
Findings
Framework allows model-independent comparison of watermarking schemes.
SSB can reach any point on the security-robustness-fidelity trade-off surface.
Theoretical guarantees eliminate the need for extensive empirical testing.
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 largely empirical, making them heavily reliant on the specific model architectures used for generation and inversion. This prevents any clear conclusion on the performance of any method, especially regarding security, for which a rigorous definition is lacking. Against this approach, we argue that the effectiveness of a watermarking scheme should be established purely through a thorough theoretical analysis. This is enabled by decoupling the model-dependent part from the actual decision mechanism of the watermarking system. Using this decoupling, we introduce a formal evaluation framework based on security, robustness, and fidelity. This allows precise…
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