Deep Data Hiding for ICAO-Compliant Face Images: A Survey
Jefferson David Rodriguez Chivata, Davide Ghiani, Simone Maurizio La Cava, Marco Micheletto, Giulia Orr\`u, Federico Lama, Gian Luca Marcialis

TL;DR
This survey reviews digital watermarking and steganography techniques for embedding tamper-evident signals into ICAO-compliant face images, enhancing post-capture security against morphing and deepfakes in identity verification systems.
Contribution
It provides the first comprehensive analysis of state-of-the-art digital watermarking and steganography methods tailored for ICAO-compliant facial images, assessing their effectiveness and limitations.
Findings
Digital watermarking can enable persistent verification of face images.
Steganography techniques offer complementary security features.
Trade-offs exist between robustness, imperceptibility, and compliance constraints.
Abstract
ICAO-compliant facial images, initially designed for secure biometric passports, are increasingly becoming central to identity verification in a wide range of application contexts, including border control, digital travel credentials, and financial services. While their standardization enables global interoperability, it also facilitates practices such as morphing and deepfakes, which can be exploited for harmful purposes like identity theft and illegal sharing of identity documents. Traditional countermeasures like Presentation Attack Detection (PAD) are limited to real-time capture and offer no post-capture protection. This survey paper investigates digital watermarking and steganography as complementary solutions that embed tamper-evident signals directly into the image, enabling persistent verification without compromising ICAO compliance. We provide the first comprehensive analysis…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
