Fragile Watermarking for Image Certification Using Deep Steganographic Embedding
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Abstract (arXiv)
Modern identity verification systems increasingly rely on facial images embedded in biometric documents such as electronic passports. To ensure global interoperability and security, these images must comply with strict standards defined by the International Civil Aviation Organization (ICAO), which specify acquisition, quality, and format requirements. However, once issued, these images may undergo unintentional degradations (e.g., compression, resizing) or malicious manipulations (e.g., morphing) and deceive facial recognition systems. In this study, we explore fragile watermarking, based on deep steganographic embedding as a proactive mechanism to certify the authenticity of ICAO-compliant facial images. By embedding a hidden image within the official photo at the time of issuance, we establish an integrity marker that becomes sensitive to any post-issuance modification. We assess how a range of image manipulations affects the recovered hidden image and show that degradation artifacts can serve as robust forensic cues. Furthermore, we propose a classification framework that analyzes the revealed content to detect and categorize the type of manipulation applied. Our experiments demonstrate high detection accuracy, including cross-method scenarios with multiple deep steganography-based models. These findings support the viability of fragile watermarking via steganographic embedding as a valuable tool for biometric document integrity verification.
Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 8 of its 31 references that are in the map. First posted on arXiv 18 Apr 2025.
Builds on
8 of 31 references.
References · 8
- 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
- 2018HiDDeN: Hiding Data With Deep Networkscited by 397
- 2023EditGuard: Versatile Image Watermarking for Tamper Localization and Copyright Protectioncited by 111
- 2020Face Image Quality Assessment: A Literature Surveycited by 80
- 2019SteganoGAN: High Capacity Image Steganography with GANscited by 72
- 2020Face Morphing Attack Generation & Detection: A Comprehensive Surveycited by 64
- 2021Data Hiding with Deep Learning: A Survey Unifying Digital Watermarking and Steganographycited by 24
- 20233D Face Reconstruction: the Road to Forensicscited by 7
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Citing papers per year: 2025: 1; 2026: 1.
2 papers.
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- 2022FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes
- 2026DeepSignature: Digitally Signed, Content-Encoding Watermarks for Robust and Transparent Image Authentication
- 2024Hide and Seek: How Does Watermarking Impact Face Recognition?
- 2024DIP-Watermark: A Double Identity Protection Method Based on Robust Adversarial Watermark
- 2026RecoverMark: Robust Watermarking for Localization and Recovery of Manipulated Faces
- 2024SWIFT: Semantic Watermarking for Image Forgery Thwarting
- 2024Trigger-Based Fragile Model Watermarking for Image Transformation Networks
- 2026Watermarks and Fingerprints as Soft Bindings for Content Provenance: An Open-Licence Benchmark for Images, Audio and Video