paper-with-me

홈 › Papers

Biometric Template Protection for Neural-Network-based Face Recognition Systems: A Survey of Methods and Evaluation Techniques

2021-10-11 · Vedrana Krivokuća Hahn, Sébastien Marcel

As automated face recognition applications tend towards ubiquity, there is a growing need to secure the sensitive face data used within these systems. This paper presents a survey of biometric template protection (BTP) methods proposed for securing face templates (images/features) in neural-network-based face recognition systems. The BTP methods are categorised into two types: Non-NN and NN-learned. Non-NN methods use a neural network (NN) as a feature extractor, but the BTP part is based on a non-NN algorithm, whereas NN-learned methods employ a NN to learn a protected template from the unprotected template. We present examples of Non-NN and NN-learned face BTP methods from the literature, along with a discussion of their strengths and weaknesses. We also investigate the techniques used to evaluate these methods in terms of the three most common BTP criteria: recognition accuracy, irreversibility, and renewability/unlinkability. The recognition accuracy of protected face recognition systems is generally evaluated using the same (empirical) techniques employed for evaluating standard (unprotected) biometric systems. However, most irreversibility and renewability/unlinkability evaluations are found to be based on theoretical assumptions/estimates or verbal implications, with a lack of empirical validation in a practical face recognition context. So, we recommend a greater focus on empirical evaluations to provide more concrete insights into the irreversibility and renewability/unlinkability of face BTP methods in practice. Additionally, an exploration of the reproducibility of the studied BTP works, in terms of the public availability of their implementation code and evaluation datasets/procedures, suggests that it would be difficult to faithfully replicate most of the reported findings. So, we advocate for a push towards reproducibility, in the hope of advancing face BTP research.

📄 PDF Abstract BibTeX arXiv:2110.05044

Code (0)

등록된 구현이 없습니다.

Tasks

Face Recognition

Similar Papers 제목 키워드 기반

Deep Learning in the Field of Biometric Template Protection: An Overview

2023-03-05 · Christian Rathgeb, Jascha Kolberg, Andreas Uhl, Christoph Busch

Today, deep learning represents the most popular and successful form of machine learning. Deep learning has revolutionised the field of pattern recognition, including biometric recognition. Biometric systems utilising de…

Deep LearningFairnessPrivacy Preserving

Feature Fusion Methods for Indexing and Retrieval of Biometric Data: Application to Face Recognition with Privacy Protection

2021-07-27 · Pawel Drozdowski, Fabian Stockhardt, Christian Rathgeb, Dailé Osorio-Roig 외

Computationally efficient, accurate, and privacy-preserving data storage and retrieval are among the key challenges faced by practical deployments of biometric identification systems worldwide. In this work, a method of …

Face RecognitionPrivacy PreservingRetrieval

A Novel Approach For Generating Face Template Using Bda

2013-12-31 · Shraddha S. Shinde, Prof. Anagha P. Khedkar

In identity management system, commonly used biometric recognition system needs attention towards issue of biometric template protection as far as more reliable solution is concerned. In view of this biometric template p…

Management

Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption

2024-04-24 · Bharat Yalavarthi, Arjun Ramesh Kaushik, Arun Ross, Vishnu Boddeti 외

Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templates in a face recognition system. These…

Face Recognition

General Framework to Evaluate Unlinkability in Biometric Template Protection Systems

2023-11-08 · Marta Gomez-Barrero, Javier Galbally, Christian Rathgeb, Christoph Busch

The wide deployment of biometric recognition systems in the last two decades has raised privacy concerns regarding the storage and use of biometric data. As a consequence, the ISO/IEC 24745 international standard on biom…