Buy article PDF
The purchased file will be sent to you
via email after the payment is completed.
US$ 35
|
Smart Structures and Systems Volume 38, Number 1, July 2026 (Special Issue) pages 57-68 📚 VSI DOI: https://doi.org/10.12989/sss.2026.38.1.057 |
|
|
|
Artificial intelligence-driven structural vulnerability analysis of ridge orientation fields in fingerprint recognition systems |
||
Enshirah Altarawneh, Jawdat S. Alkasassbeh, Khalaf Y. Alzyoud, Sattam Almatarneh, Redhwan Algabri
|
||
| Abstract | ||
| The primary structural element used by fingerprint recognition systems is the ridge orientation structure which provides a geometric prior for enhancing images, extracting features and comparing them to one another. However, most of the previous adversarial studies have operated in the pixel domain and therefore, structural manipulation within the orientation manifold has been left mostly unexplored. Therefore, we introduce a ridge orientation perturbation framework that is constrained based on ridge flow characteristics such that the generated perturbations preserve the smoothness and singularity properties of the original ridge flows. In doing so, we ensure that our attacks are biometrically plausible but induce instability to the verification process. We tested the proposed attack on controlled (FVC2004) and forensic latent (NIST SD27) databases using both classical minutiae-based and CNNbased matchers. Our experimental results show that severe degradation can be achieved when structurally consistent perturbations are applied, where the equal error rate (EER) increased on the NIST SD27 database. Our findings indicate that ridge orientations represent a critical structural component of fingerprint systems that is shared across multiple recognition paradigms and illustrate a previously under-characterized geometric vulnerability. | ||
| Key Words | ||
| Adversarial biometrics; Attack Success Rate (ASR); biometric security; Equal Error Rate (EER); fingerprint recognition; minutiae-based matching; ridge orientation perturbation; ROC analysis | ||
| Address | ||
| (1) Enshirah Altarawneh: Department of Computer Engineering, Faculty of Engineering, The Hashemite University, Zarqa, Jordan; (2) Jawdat S. Alkasassbeh, Khalaf Y. Alzyoud: Department of Electrical Engineering, Faculty of Engineering Technology, Al-Balqa Applied University, Amman, Jordan; (3) Sattam Almatarneh: Faculty of Information Technology, Zarqa University, Zarqa, Jordan; (4) Redhwan Algabri: Department of Computer Science and Engineering, Sejong University, Seoul, 05006, Republic of Korea. | ||