DiffVax: Optimization-Free Image Immunization Against Diffusion-Based Editing
Tarik Can Ozden, Ozgur Kara, Oguzhan Akcin, Kerem Zaman, Shashank Srivastava, Sandeep P. Chinchali, James M. Rehg

TL;DR
DiffVax is a scalable, optimization-free image immunization framework that effectively prevents diffusion-based editing with minimal computational cost, generalizing well to unseen content and protecting videos.
Contribution
We introduce DiffVax, a novel, optimization-free approach that significantly reduces immunization time and enhances scalability against diffusion-based editing attacks.
Findings
Reduces immunization time from days to milliseconds
Achieves 250,000x speedup over previous methods
Effectively protects both images and videos from editing
Abstract
Current image immunization defense techniques against diffusion-based editing embed imperceptible noise into target images to disrupt editing models. However, these methods face scalability challenges, as they require time-consuming optimization for each image separately, taking hours for small batches. To address these challenges, we introduce DiffVax, a scalable, lightweight, and optimization-free framework for image immunization, specifically designed to prevent diffusion-based editing. Our approach enables effective generalization to unseen content, reducing computational costs and cutting immunization time from days to milliseconds, achieving a speedup of 250,000x. This is achieved through a loss term that ensures the failure of editing attempts and the imperceptibility of the perturbations. Extensive qualitative and quantitative results demonstrate that our model is scalable,…
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Taxonomy
TopicsImage Processing Techniques and Applications · Advanced Steganography and Watermarking Techniques
