Foundations and Frontiers of Watermarking: Algorithms, Multimodal Extensions, Benchmarks, and Authenticity Frameworks

Watermarking has re-emerged as a critical component of trustworthy AI, driven by the rapid growth of generative models and the need for content attribution and authenticity. This tutorial provides a unified overview of watermarking, spanning classical signal-processing foundations and modern deep-learning–based approaches across images, video, audio, and multimodal data. It examines key challenges such as robustness, capacity, and adversarial resilience, along with recent benchmarking efforts and evaluation frameworks. The tutorial further connects these methods to real-world deployment through applications in content provenance, media forensics, and emerging standards such as C2PA, offering a comprehensive perspective on building reliable and transparent media systems.