IMSE Publications

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Author: Paula López González
Year: Since 2002

Journal Papers


Evaluation of a Vein Biometric Recognition System on an Ordinary Smartphone
P. López-González, I. Baturone, M. Hinojosa and R. Arjona
Journal Paper · Applied Sciences, vol. 12, no. 7, article 3522, 2022
abstract      doi      

Nowadays, biometrics based on vein patterns as a trait is a promising technique. Vein patterns satisfy universality, distinctiveness, permanence, performance, and protection against circumvention. However, collectability and acceptability are not completely satisfied. These two properties are directly related to acquisition methods. The acquisition of vein images is usually based on the absorption of near-infrared (NIR) light by the hemoglobin inside the veins, which is higher than in the surrounding tissues. Typically, specific devices are designed to improve the quality of the vein images. However, such devices increase collectability costs and reduce acceptability. This paper focuses on using commercial smartphones with ordinary cameras as potential devices to improve collectability and acceptability. In particular, we use smartphone applications (apps), mainly employed for medical purposes, to acquire images with the smartphone camera and improve the contrast of superficial veins, as if using infrared LEDs. A recognition system has been developed that employs the free IRVeinViewer App to acquire images from wrists and dorsal hands and a feature extraction algorithm based on SIFT (scale-invariant feature transform) with adequate pre- and post-processing stages. The recognition performance has been evaluated with a database composed of 1000 vein images associated to five samples from 20 wrists and 20 dorsal hands, acquired at different times of day, from people of different ages and genders, under five different environmental conditions: day outdoor, indoor with natural light, indoor with natural light and dark homogeneous background, indoor with artificial light, and darkness. The variability of the images acquired in different sessions and under different ambient conditions has a large influence on the recognition rates, such that our results are similar to other systems from the literature that employ specific smartphones and additional light sources. Since reported quality assessment algorithms do not help to reject poorly acquired images, we have evaluated a solution at enrollment and matching that acquires several images subsequently, computes their similarity, and accepts only the samples whose similarity is greater than a threshold. This improves the recognition, and it is practical since our implemented system in Android works in real-time and the usability of the acquisition app is high.

Conferences


A Facial Authentication System using Post-Quantum-Secure Data Generated on Mobile Devices
P. López-González, R. Arjona, R. Román and I. Baturone
Conference · International Conference on Mobile Computing and Networking MOBICOM 2022
abstract     

This paper describes a demonstrator of a post-quantum-secure facial authentication system distributed between a mobile device acting as a client and a remote computer acting as an authentication server. Homomorphic encryption based on Classic McEliece, one of the fourth-round candidates of the NIST post-quantum standardization process, is carried out by the client for protecting the biometric data extracted from the users’ faces at enrollment and verification. The remote computer only stores and compares the received protected data, thus preserving user privacy. An Android App and a Graphical User Interface (GUI) were implemented at the client and the server, respectively, to show the system performance in terms of computation and security.

A Quantum-Resistant Face Template Protection Scheme using Kyber and Saber Public Key Encryption Algorithms
R. Roman, R. Arjona, P. Lopez-Gonzalez, I. Baturone, A. Bromme, N. Damer, M. Gomez-Barrero, K. Raja, C. Rathgeb, A.F. Sequeira, M. Todisco and A. Uhl
Conference · Conference of the Biometrics-Special-Interest-Group BIOSIG 2022
abstract     

Considered sensitive information by the ISO/IEC 24745, biometric data should be stored and used in a protected way. If not, privacy and security of end-users can be compromised. Also, the advent of quantum computers demands quantum-resistant solutions. This work proposes the use of Kyber and Saber public key encryption (PKE) algorithms together with homomorphic encryption (HE) in a face recognition system. Kyber and Saber, both based on lattice cryptography, were two finalists of the third round of NIST post-quantum cryptography standardization process. After the third round was completed, Kyber was selected as the PKE algorithm to be standardized. Experimental results show that recognition performance of the non-protected face recognition system is preserved with the protection, achieving smaller sizes of protected templates and keys, and shorter execution times than other HE schemes reported in literature that employ lattices. The parameter sets considered achieve security levels of 128, 192 and 256 bits.

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