TarPro: Targeted Protection against Malicious Image Editing
This addresses the need for secure and controlled image editing to prevent misuse, representing an incremental improvement over existing methods that fail to balance protection and editability.
The paper tackles the problem of malicious image editing for generating NSFW content by proposing TarPro, a targeted protection framework that prevents harmful edits while preserving normal editability, achieving high protection efficacy with minimal impact on benign modifications.
The rapid advancement of image editing techniques has raised concerns about their misuse for generating Not-Safe-for-Work (NSFW) content. This necessitates a targeted protection mechanism that blocks malicious edits while preserving normal editability. However, existing protection methods fail to achieve this balance, as they indiscriminately disrupt all edits while still allowing some harmful content to be generated. To address this, we propose TarPro, a targeted protection framework that prevents malicious edits while maintaining benign modifications. TarPro achieves this through a semantic-aware constraint that only disrupts malicious content and a lightweight perturbation generator that produces a more stable, imperceptible, and robust perturbation for image protection. Extensive experiments demonstrate that TarPro surpasses existing methods, achieving a high protection efficacy while ensuring minimal impact on normal edits. Our results highlight TarPro as a practical solution for secure and controlled image editing.