This research paper introduces RDIAS, a novel image authentication system designed to combat the increasing sophistication of AI-powered image manipulation. RDIAS embeds robust, tamper-evident fingerprints into images using deep learning techniques, preserving image quality while detecting malicious alterations. The system is evaluated extensively against various realistic manipulations and transformations, demonstrating high accuracy and real-time performance. A key focus is on robustness to common social media platform operations that invalidate existing authentication methods. In this work, we analyzed various perceptual hashing, watermarking, and error-correcting code methods, selecting optimal components for RDIAS based on rigorous testing.
Attacked Images in our Human Evaluation can be found in the following link:
https://drive.google.com/drive/folders/1aNiVwwZQ7FBed2UD_RaZV7KBf_Df5RcS?usp=drive_link
- In Proceedings of the ACM Transactions on Multimedia Computing, Communications, and Applications; 2025.