A Generalized Approach for Cancellable Template and Its Realization for
Minutia Cylinder-Code
- URL: http://arxiv.org/abs/2203.01095v1
- Date: Wed, 2 Mar 2022 13:30:46 GMT
- Title: A Generalized Approach for Cancellable Template and Its Realization for
Minutia Cylinder-Code
- Authors: Xingbo Dong, Zhe Jin and KokSheik Wong
- Abstract summary: Index-of-Max (IoM) is a ranking-based locality sensitive hashing technique.
biometric templates are not always in the form of ordered and fixed-length, rather it may be an unordered and variable size point set.
We propose a generalized version of IoM hashing namely gIoM, and therefore the unordered and variable size biometric template can be used.
- Score: 11.442790699169363
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Hashing technology gains much attention in protecting the biometric template
lately. For instance, Index-of-Max (IoM), a recent reported hashing technique,
is a ranking-based locality sensitive hashing technique, which illustrates the
feasibility to protect the ordered and fixed-length biometric template.
However, biometric templates are not always in the form of ordered and
fixed-length, rather it may be an unordered and variable size point set e.g.
fingerprint minutiae, which restricts the usage of the traditional hashing
technology. In this paper, we proposed a generalized version of IoM hashing
namely gIoM, and therefore the unordered and variable size biometric template
can be used. We demonstrate a realization using a well-known variable size
feature vector, fingerprint Minutia Cylinder-Code (MCC). The gIoM transforms
MCC into index domain to form indexing-based feature representation.
Consequently, the inversion of MCC from the transformed representation is
computational infeasible, thus to achieve non-invertibility while the
performance is preserved. Public fingerprint databases FVC2002 and FVC2004 are
employed for experiment as benchmark to demonstrate a fair comparison with
other methods. Moreover, the security and privacy analysis suggest that gIoM
meets the criteria of template protection: non-invertibility, revocability, and
non-linkability.
Related papers
- A secure and private ensemble matcher using multi-vault obfuscated templates [1.3518297878940662]
Generative AI has revolutionized modern machine learning by providing unprecedented realism, diversity, and efficiency in data generation.
Biometric template security and secure matching are among the most sought-after features of modern biometric systems.
This paper proposes a novel obfuscation method using Generative AI to enhance biometric template security.
arXiv Detail & Related papers (2024-04-08T05:18:39Z) - Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation [49.827306773992376]
Continual Test-Time Adaptation (CTTA) is proposed to migrate a source pre-trained model to continually changing target distributions.
Our proposed method attains state-of-the-art performance in both classification and segmentation CTTA tasks.
arXiv Detail & Related papers (2023-12-19T15:34:52Z) - Large-scale gradient-based training of Mixtures of Factor Analyzers [67.21722742907981]
This article contributes both a theoretical analysis as well as a new method for efficient high-dimensional training by gradient descent.
We prove that MFA training and inference/sampling can be performed based on precision matrices, which does not require matrix inversions after training is completed.
Besides the theoretical analysis and matrices, we apply MFA to typical image datasets such as SVHN and MNIST, and demonstrate the ability to perform sample generation and outlier detection.
arXiv Detail & Related papers (2023-08-26T06:12:33Z) - Towards General Visual-Linguistic Face Forgery Detection [95.73987327101143]
Deepfakes are realistic face manipulations that can pose serious threats to security, privacy, and trust.
Existing methods mostly treat this task as binary classification, which uses digital labels or mask signals to train the detection model.
We propose a novel paradigm named Visual-Linguistic Face Forgery Detection(VLFFD), which uses fine-grained sentence-level prompts as the annotation.
arXiv Detail & Related papers (2023-07-31T10:22:33Z) - OTB-morph: One-Time Biometrics via Morphing [16.23764869038004]
This paper introduces a new idea to exploit as a transformation function for cancelable biometrics.
An experimental implementation of the proposed scheme is given for face biometrics.
arXiv Detail & Related papers (2023-02-17T18:39:40Z) - An Accelerated Doubly Stochastic Gradient Method with Faster Explicit
Model Identification [97.28167655721766]
We propose a novel doubly accelerated gradient descent (ADSGD) method for sparsity regularized loss minimization problems.
We first prove that ADSGD can achieve a linear convergence rate and lower overall computational complexity.
arXiv Detail & Related papers (2022-08-11T22:27:22Z) - OTB-morph: One-Time Biometrics via Morphing applied to Face Templates [8.623680649444212]
This paper introduces a new scheme for cancelable biometrics aimed at protecting the templates against potential attacks.
An experimental implementation of the proposed scheme is given for face biometrics.
arXiv Detail & Related papers (2021-11-25T18:35:34Z) - Feature Fusion Methods for Indexing and Retrieval of Biometric Data:
Application to Face Recognition with Privacy Protection [15.834050000008878]
The proposed method reduces the computational workload associated with a biometric identification transaction by 90%.
The method guarantees unlinkability, irreversibility, and renewability of the protected biometric data.
arXiv Detail & Related papers (2021-07-27T08:53:29Z) - Random Hash Code Generation for Cancelable Fingerprint Templates using
Vector Permutation and Shift-order Process [3.172761915061083]
We propose a non-invertible distance preserving scheme based on vector permutation and shift-order process.
A shift-order process is then applied to the generated features in order to achieve non-invertibility and combat similarity-based attacks.
The generated hash codes are resilient to different security and privacy attacks whilst fulfilling the major revocability and unlinkability requirements.
arXiv Detail & Related papers (2021-05-21T09:37:54Z) - SMT-based Safety Verification of Parameterised Multi-Agent Systems [78.04236259129524]
We study the verification of parameterised multi-agent systems (MASs)
In particular, we study whether unwanted states, characterised as a given state formula, are reachable in a given MAS.
arXiv Detail & Related papers (2020-08-11T15:24:05Z) - Understanding Implicit Regularization in Over-Parameterized Single Index
Model [55.41685740015095]
We design regularization-free algorithms for the high-dimensional single index model.
We provide theoretical guarantees for the induced implicit regularization phenomenon.
arXiv Detail & Related papers (2020-07-16T13:27:47Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.