As AI-generated content becomes more prevalent, ensuring authenticity, ownership, and traceability is increasingly critical in the landscape of content creation and distribution. Generative watermarking, an innovative approach, involves embedding invisible or detectable markers directly into AI-generated text, images, audio, and video. This technique allows content to be traced back to its origin which is essential for verifying authorship and protecting intellectual property. Unlike traditional watermarking that is applied post-creation, generative watermarking integrates content protection directly into the generative AI model itself.

The field of generative watermarking involves employing advanced signal processing techniques to integrate watermarks within digital media. Transform Domain Watermarking is one such approach, utilizing techniques like Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT), and Fourier Transform to embed watermarks directly into content. Despite ongoing innovation, ensuring robustness against signal manipulation remains a challenge. Researchers are actively exploring methods to make watermarks resistant to operations such as compression, scaling, cropping, and noise addition.

This Research Topic aims to explore the development of watermarking methods. Specifically, we seek to explore how watermarking can maintain its integrity across various file formats. This research aspires to promote standardized verification protocols to enhance digital provenance while encouraging collaboration across industries to protect creators without stifling innovation.

To gather further insights in the domain of generative watermarking, we welcome articles addressing, but not limited to, the following themes:
- Implementation of robust, transformative watermarking techniques in varied media formats.
- Advances in adaptive algorithm development for dynamic watermark parameter adjustment.
- Cryptographic and AI-enabled enhancements for watermark security.
- Exploration and comparison of blind versus non-blind watermarking methods.
- Seamless integration of watermarking with DRM systems for content protection.
- Real-time generation and detection of watermarks in live and streaming applications.
- Effective strategies for watermarking in multi-format media environments.
- Innovative methods to enhance watermark resilience against compression and other signal manipulations.
- Addressing challenges in watermark detection for distinguishing deepfakes and synthetic media.
- Strengthening watermarks to resist adversarial attacks and tampering efforts.

Frontiers in Signal Processing is a contributor to the 2025 Top 10 Emerging Technologies Report launched at the WEF Annual Meeting of the New Champions in Tianjin in June 2025. This Research Topic highlights one of the featured technologies and aims to foster community collaboration around its development and impact. You can read the full report here : https://www.weforum.org/publications/top-10-emerging-technologies-of-2025/

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Generative Watermarking: A Frontier in Protecting AI-Generated Content Authenticity