Fragile Watermarking

Fragile watermarking techniques embed hidden information into data (images, models, etc.) that is easily destroyed by tampering, thus providing a verifiable proof of integrity. Current research focuses on developing robust yet fragile watermarks for various applications, including detecting deepfakes and malicious modifications in AI models, often employing deep learning architectures like generative adversarial networks (GANs) and encoder-decoder networks to achieve high accuracy and resilience to certain attacks. This field is crucial for ensuring the authenticity and trustworthiness of digital media and AI systems, addressing growing concerns about misinformation and malicious manipulation.