PrivateSeal: Low-Sensitivity Latent Directions for Diffusion-Resilient User-Specific Watermarking

Diffusion-driven image editing and regeneration are becoming increasingly widespread. This creates an urgent need for watermarking methods that can embed imperceptible yet verifiable signals into existing images for ownership attribution and provenance tracking. Existing methods fail to simultaneously satisfy three practical requirements: robustness against diffusion-based transformations, low-cost verification, and scalable support for per-user key assignment at low overhead. To address these challenges, we propose PrivateSeal, a watermarking framework for pre-existing images under diffusion-based transformations. The perturbation is encouraged to lie along low-sensitivity latent directions, so that the embedded signal is less likely to be suppressed during diffusion-based editing or regeneration. During verification, the embedded message is reliably recovered via a simple latent-space projection using the corresponding key. This design allows a platform to assign independent projection keys to different users, accounts, or images without retraining or modifying the verifier, while maintaining low-cost verification. Extensive experiments on the W-Bench benchmark show that PrivateSeal achieves competitive robustness against diffusion-based regeneration and editing, with additional cross-model and cross-dataset evaluations further validating its strong transferability.