Adversarial Watermarking

Adversarial watermarking focuses on embedding imperceptible identifiers into digital data (images, audio, models) to prove ownership and deter unauthorized use, while simultaneously making the watermark robust against attacks aiming to remove or alter it. Current research emphasizes developing watermarking techniques resistant to sophisticated attacks, including those leveraging generative adversarial networks (GANs) and diffusion models, often employing contrastive learning and adversarial training methods to enhance robustness. This field is crucial for protecting intellectual property in various domains, from media authentication and copyright enforcement to securing the integrity of machine learning models and preventing misuse of sensitive data.