Enhancing the Security of Transformation Based Biometric Template Protection Schemes

Ghammam, Loubna; Barbier, Morgan; Rosenberger, Christophe

doi:10.1109/cw.2018.00065

Cited by 12 publications

(2 citation statements)

References 26 publications

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“…Another variation, "Indexof-Max" (IoM) hashing, developed by Jin et al, converts real-value biometric feature vectors into discrete indexed hashed codes, yielding an EER of 4.10% in the stolen token scenario (208). Additionally, Morgan et al introduced a transformation function effective against specific attacks, embedding biometric data into an orthogonalized pseudorandom numeric matrix created using a secret key or token and nonlinear operations, with an EER of 0.4% at a GAR of 99% (218).…”

Section: A Feature Transformationmentioning

confidence: 99%

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Sumalatha,

Prakasha,

Prabhu

et al. 2024

IEEE Access

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In the contemporary technological landscape, biometrics, encompassing the analysis of biological data, have gained significance. Biometrics is a methodology that utilize unique behavioral, physical, or morphological traits-such as speech, facial features, iris, fingerprint, retina, and signature for individual identification. Biometric technology has been successfully used in forensic science, security, and authorization systems. This review highlights understanding the classification, types of biometric traits and their comparisons, fingerprint recognition stands out as a reliable and widely adopted method due to its simplicity and cost-effectiveness, accuracy and robustness compared to others. Unimodal fingerprint biometric systems safeguard authentication information through the analysis of characteristic sequences and, face challenges such as vulnerability to spoof attacks, inter-class similarity, intra-class variation, non-universality, and noisy data. These challenges are addressed by multimodal fingerprint biometric systems, in which various biometric sources compensate for each other's limitations. The review focuses on the overview of unimodal and multimodal fingerprint biometric systems and the importance of fusion, advancements in data acquisition, preprocessing, feature extraction, matching algorithms, performance metrics, indexing, template protection, and addressing attacks in enhancing system security and reliability. The review paper sheds light on the intricate relationship between these elements, offering valuable insights into the current state and potential evolution of the field. The review paper highlights current challenges and suggests future research directions, emphasizing the necessity for continual advancements in fusion techniques, template protection methods, and novel defense mechanisms to effectively mitigate emerging threats in unimodal and multimodal fingerprint biometric systems.

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Section: A Feature Transformationmentioning

confidence: 99%

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Sumalatha,

Prakasha,

Prabhu

et al. 2024

IEEE Access

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“…A template protection technique that meets these specifications is essential in privacy-preserving approaches. Several classifications exist for template protection schemes [ 85 , 86 ]. For the sake of simplicity, the one proposed in [ 84 ] is considered: Cancelable Biometrics/Feature Transformation : This concept refers to the use of deliberately distorted biometric features to generate disrupted versions of the template.…”

Section: Privacy-preserving Approachesmentioning

confidence: 99%

Privacy-Preserving Sensor-Based Continuous Authentication and User Profiling: A Review

Hernández–Álvarez

Fuentes

González-Manzano

et al. 2020

Sensors

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Ensuring the confidentiality of private data stored in our technological devices is a fundamental aspect for protecting our personal and professional information. Authentication procedures are among the main methods used to achieve this protection and, typically, are implemented only when accessing the device. Nevertheless, in many occasions it is necessary to carry out user authentication in a continuous manner to guarantee an allowed use of the device while protecting authentication data. In this work, we first review the state of the art of Continuous Authentication (CA), User Profiling (UP), and related biometric databases. Secondly, we summarize the privacy-preserving methods employed to protect the security of sensor-based data used to conduct user authentication, and some practical examples of their utilization. The analysis of the literature of these topics reveals the importance of sensor-based data to protect personal and professional information, as well as the need for exploring a combination of more biometric features with privacy-preserving approaches.

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Fingerprint—A Survey on Feature Transformation

Mohsin

Bharti

2022

Advances in Intelligent Systems and Computing

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Enhancing the Security of Transformation Based Biometric Template Protection Schemes

Cited by 12 publications

References 26 publications

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

A Comprehensive Review of Unimodal and Multimodal Fingerprint Biometric Authentication Systems: Fusion, Attacks, and Template Protection

Privacy-Preserving Sensor-Based Continuous Authentication and User Profiling: A Review

Fingerprint—A Survey on Feature Transformation

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