Multi-biometric Template Protection: An Overview

Bedad, Fatima; Adjoudj, Reda

doi:10.1007/978-3-030-04789-4_7

Cited by 5 publications

(4 citation statements)

References 11 publications

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“…As mentioned in the preceding section, the limited protection of multi-modal systems, the biometric template drawbacks of security techniques, and the impracticality of the identification algorithms used in these cases have encouraged searchers to explore the chances to successfully combine these two areas. From the scientific viewpoint, the protection of a multi-biometric template has multiple aspects [6].…”

Section: Related Workmentioning

confidence: 99%

“…Several studies or experimental approaches that focus on the most widely used biometric data (fingerprint, iris, ,face) and goal to reduce mistakes provinding increased protection [9], [13], [14]. Table 1 summarizes the most remarkable work, according to current methods, aimed at securing the multi-biometric model [6] .…”

Section: Related Workmentioning

confidence: 99%

“…The BioHashing algorithm remains yet the well-known method, which is focused on biometric data revocable. It has been designed for various biometric templates [5], [6].…”

Section: Introductionmentioning

confidence: 99%

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Studies of the Robustness of a Transformation-Based Multi-Biometric Template Schemes Protection

Bedad¹,

Adjoudj²,

Bousahba³

2022

IJCDS

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As the number of applications that use multimodal biometrics grows, potential challenges to privacy and protection emerge. New multi-biometric technologies have been suggested in the context of privacy and confidentiality: template protection systems. For the relevant defensive technologies, very current solutions have been presented. Their decision on the optimal strategy is still being considered. This paper provides an evaluation of multi-biometric protection systems according to a transformation proposing some measures and metrics to test its performances and sturdiness faced against attacks. These measures enable evaluating the success of the approach in various scenarios. In this perspective, this article proposes a transformation-based multi-modal biometric protection system that focuses on BioHashing by merging fingerprint modalities. The fingerprint images are classified into three instances and represented by a feature vector using a 2D Log-Gabor filter. A biohashing is applied to its vectors to create Biocode vectors. Following that, a multi-instance score fusion formed by Biocodes of the fingerprints is merged at the matching level. Finally, to get a high score, multi-sample score fusion is used. Furthermore, a transformation-based protection model that focuses on BioHashing demonstrates how specific security and privacy may be validated.

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Studies of the Robustness of a Transformation-Based Multi-Biometric Template Schemes Protection

Bedad¹,

Adjoudj²,

Bousahba³

2022

IJCDS

Self Cite

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“…These biometrics depend on the body shape such as mouth, skull, heart muscles, brain gyrus shape, and body molecule. They also depend on the circumstances and the different reactions which vary from one person to another [4]. Biometrics are effective in verifying and authentication systems.…”

Section: Introductionmentioning

confidence: 99%

Efficient Implementation of Double Random Phase Encoding and Empirical Mode Decomposition for Cancelable Biometrics

Salama

El‐Shafai

El‐Gazar

et al. 2023

Preprint

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Safe access to essential systems using biometrics has gained increasing attention in the last decades. Biometrics need to be saved in a protected template away from hackers. They can be saved in a cancelable template that can be replaced in hacking scenarios. In this paper, a unimodal cancelable biometric system is introduced. Bio-signals are the biometrics signals such as voiceprint, Electroencephalography, and Electrocardiography that are tested by the proposed system. This proposed system depends on the Empirical Mode Decomposition (EMD). EMD is used to decompose the bio-signal into different intrinsic mode functions (IMFs). The first IMF carries most of the signal energy that distinguishes the bio-signal. The encryption algorithm has an essential role in cancelable template generation. Double Random Phase Encoding (DRPE) with its Random Phase Masks (RPM) is used to encrypt the first IMF after converting to 2-D format. DRPE with its random masks can be considered a non-invertible transformation. A reference signal is used to be a cover signal for the encrypted first IMF. However, the first IMF of the reference signal is replaced by the encrypted first IMF of the bio-signal to obtain the cancelable template. The verification process is performed by matching the saved first IMF and the new first IMF in their encrypted forms. Simulation analysis indicates the high performance of the proposed system. Different metrics have been investigated to evaluate the proposed system such as Equal Error Rate (EER) and Area under Receiver Operator Characteristic (AROC). This system proves its stability in the presence of different levels of white Gaussian noise where the EER is close to 0 and the AROC is close to 1.

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