Watermark Attack

Watermark attacks target methods used to embed hidden identifiers (watermarks) in digital content, such as images or text generated by AI models, to verify authenticity and ownership. Current research focuses on developing more robust watermarking techniques, particularly against attacks leveraging advanced generative models like diffusion models and language models, and exploring novel approaches like watermarking in latent spaces or implicit neural representations. This field is crucial for protecting intellectual property in the age of readily available image and text manipulation tools, with implications for copyright enforcement, content attribution, and the broader fight against misinformation.