Cancelable biometrics (CB) employs an irreversible transformation to convert the biometric features into transformed templates while preserving the relative distance between two templates for security and privacy protection. However, distance preservation invites unexpected security issues such as pre-image attacks, which are often neglected.This paper presents a generalized pre-image attack method and its extension version that operates on practical CB systems. We theoretically reveal that distance preservation property is a vulnerability source in the CB schemes. We then propose an empirical information leakage estimation algorithm to access the pre-image attack risk of the CB schemes. The experiments conducted with six CB schemes designed for the face, iris and fingerprint, demonstrate that the risks originating from the distance computed from two transformed templates significantly compromise the security of CB schemes. Our work reveals the potential risk of existing CB systems theoretically and experimentally.
Indian Institute of Technology Indore（印度理工学院印多尔分校）
In a biometric verification system, leakage of biometric data leads to permanent identity loss since original biometric data is inherently linked to a user. Further, various types of attacks on a biometric system may reveal the original template and utility in other applications. To address these security and privacy concerns cancelable biometric has been introduced. Cancelable biometric constructs a protected template from the original biometric template using transformation functions and performs the comparison between templates in the transformed domain. Recent approaches towards cancelable…
Monash University Malaysia（莫纳什大学马来西亚校区）；Electronics and Telecommunications Research Institute（韩国电子通信研究院）；Yonsei University（延世大学）
In this paper, we propose a ranking based locality sensitive hashing inspired two-factor cancelable biometrics, dubbed "Index-of-Max" (IoM) hashing for biometric template protection. With externally generated random parameters, IoM hashing transforms a real-valued biometric feature vector into discrete index (max ranked) hashed code. We demonstrate two realizations from IoM hashing notion, namely Gaussian Random Projection based and Uniformly Random Permutation based hashing schemes. The discrete indices representation nature of IoM hashed codes enjoy serveral merits. Firstly, IoM hashing empo…
School of Cyber Science and Engineering, Southeast University（东南大学计算机科学与工程学院）；Engineering Research Center of Blockchain Application, Supervision and Management (Southeast University), Ministry of Education（教育部区块链应用监督与管理工程研究中心（东南大学））；Purple Mountain Laboratories（紫金山实验室）；College of Computer, Nanjing University of Posts and Telecommunications（南京邮电大学计算机学院）；Department of Computer and Information Science, University of Macao（澳门大学计算机与信息科学系）；Department of Computer Science and Engineering, The Hong Kong University of Science and Technology（香港科学与技术大学计算机科学与工程系）
School of Engineering Technology, SUNY at Farmingdale（纽约州立大学法明代尔分校工程技术学院）
Fingerprint is widely used in a variety of applications. Security measures have to be taken to protect the privacy of fingerprint data. Cancelable biometrics is proposed as an effective mechanism of using and protecting biometrics. In this paper we propose a new method of constructing cancelable fingerprint template by combining real template with synthetic template. Specifically, each user is given one synthetic minutia template generated with random number generator. Every minutia point from the real template is individually thrown into the synthetic template, from which its k-nearest neighb…
Indian Institute of Technology Indore（印度理工学院印多尔分校）
In spite of the benefits of biometric-based authentication systems, there are few concerns raised because of the sensitivity of biometric data to outliers, low performance caused due to intra-class variations and privacy invasion caused by information leakage. To address these issues, we propose a hybrid fusion framework where only the protected modalities are combined to fulfill the requirement of secrecy and performance improvement. This paper presents a method to integrate cancelable modalities utilizing mean-closure weighting (MCW) score level and Dempster-Shafer (DS) theory based decision…
Université Clermont-Auvergne（克莱蒙奥弗涅大学）；CNRS（法国国家科学研究中心）；Mines de Saint-Étienne（圣艾蒂安高等矿业学校）；LIMOS（图像与系统建模与优化实验室）；LMBP（布莱士·帕斯卡数学实验室）
Cancelable biometric schemes aim at generating secure biometric templates by combining user specific tokens, such as password, stored secret or salt, along with biometric data. This type of transformation is constructed as a composition of a biometric transformation with a feature extraction algorithm. The security requirements of cancelable biometric schemes concern the irreversibility, unlinkability and revocability of templates, without losing in accuracy of comparison. While several schemes were recently attacked regarding these requirements, full reversibility of such a composition in ord…
Cancelable biometric schemes generate secure biometric templates by combining user specific tokens and biometric data. The main objective is to create irreversible, unlinkable, and revocable templates, with high accuracy in matching. In this paper, we cryptanalyze two recent cancelable biometric schemes based on a particular locality sensitive hashing function, index-of-max (IoM): Gaussian Random Projection-IoM (GRP-IoM) and Uniformly Random Permutation-IoM (URP-IoM). As originally proposed, these schemes were claimed to be resistant against reversibility, authentication, and linkability attac…
With increasing concerns about security, the need for highly secure physical biometrics-based authentication systems utilizing \emph{cancelable biometric} technologies is on the rise. Because the problem of cancelable template generation deals with the trade-off between template security and matching performance, many state-of-the-art algorithms successful in generating high quality cancelable biometrics all have random projection as one of their early processing steps. This paper therefore presents a formal analysis of why random projections is an essential step in cancelable biometrics. By f…
Cancelable Biometric Template Generation Using Random Feature Vector Transformations
Indian Institute of Information Technology and Management-Kerala（印度信息技术与管理学院（喀拉拉邦））；Cochin University of Science and Technology（科钦科学技术大学）；Kerala University of Digital Sciences, Innovation and Technology（喀拉拉邦数字科学、创新与技术大学）；Singapore Institute of Technology（新加坡理工学院）
Idiap Research Institute（Idiap研究所）；École Polytechnique Fédérale de Lausanne (EPFL)（洛桑联邦理工学院）；Universidad Autonoma de Madrid (UAM)（马德里自治大学）；Hochschule Darmstadt (HDA)（达姆施塔特应用技术大学）；Norwegian University of Science and Technology (NTNU)（挪威科技大学）；Université de Lausanne (UNIL)（洛桑大学）
In this paper, we benchmark several cancelable biometrics (CB) schemes on different biometric characteristics. We consider BioHashing, Multi-Layer Perceptron (MLP) Hashing, Bloom Filters, and two schemes based on Index-of-Maximum (IoM) Hashing (i.e., IoM-URP and IoM-GRP). In addition to the mentioned CB schemes, we introduce a CB scheme (as a baseline) based on user-specific random transformations followed by binarization. We evaluate the unlinkability, irreversibility, and recognition performance (which are the required criteria by the ISO/IEC 24745 standard) of these CB schemes on deep learn…
National Institute of Advanced Industrial Science and Technology (AIST)（产业技术综合研究所）；Shizuoka University（静冈大学）；Hitachi, Ltd.（日立有限公司）
A cancelable biometric scheme called correlation-invariant random filtering (CIRF) is known as a promising template protection scheme. This scheme transforms a biometric feature represented as an image via the 2D number theoretic transform (NTT) and random filtering. CIRF has perfect secrecy in that the transformed feature leaks no information about the original feature. However, CIRF cannot be applied to large-scale biometric identification, since the 2D inverse NTT in the matching phase requires high computational time. Furthermore, existing biometric indexing schemes cannot be used in conju…
Indian Institute of Technology Indore（印度理工学院印多尔分校）
The identity of a user is permanently lost if biometric data gets compromised since the biometric information is irreplaceable and irrevocable. To revoke and reissue a new template in place of the compromised biometric template, the idea of cancelable biometrics has been introduced. The concept behind cancelable biometric is to irreversibly transform the original biometric template and perform the comparison in the protected domain. In this paper, a coprime transformation scheme has been proposed to derive a protected fingerprint template. The method divides the fingerprint region into a numbe…
Cancelable biometrics refers to a group of techniques in which the biometric inputs are transformed intentionally using a key before processing or storage. This transformation is repeatable enabling subsequent biometric comparisons. This paper introduces a new scheme for cancelable biometrics aimed at protecting the templates against potential attacks, applicable to any biometric-based recognition system. Our proposed scheme is based on time-varying keys obtained from morphing random biometric information. An experimental implementation of the proposed scheme is given for face biometrics. The …
College of Computer and Information Technology（计算机与信息学院）；China Three Gorges University（三峡大学）
Cancelable biometric techniques have been used to prevent the compromise of biometric data by generating and using their corresponding cancelable templates for user authentication. However, the non-invertible distance preserving transformation methods employed in various schemes are often vulnerable to information leakage since matching is performed in the transformed domain. In this paper, we propose a non-invertible distance preserving scheme based on vector permutation and shift-order process. First, the dimension of feature vectors is reduced using kernelized principle component analysis (…
Present world has already been consistently exploring the fine edges of online and digital world by imposing multiple challenging problems/scenarios. Similar to physical world, personal identity management is very crucial in-order to provide any secure online system. Last decade has seen a lot of work in this area using biometrics such as face, fingerprint, iris etc. Still there exist several vulnerabilities and one should have to address the problem of compromised biometrics much more seriously, since they cannot be modified easily once compromised. In this work, we have proposed a secure can…
Cancelable biometrics are a group of techniques to transform the input biometric to an irreversible feature intentionally using a transformation function and usually a key in order to provide security and privacy in biometric recognition systems. This transformation is repeatable enabling subsequent biometric comparisons. This paper is introducing a new idea to exploit as a transformation function for cancelable biometrics aimed at protecting the templates against iterative optimization attacks. Our proposed scheme is based on time-varying keys (random biometrics in our case) and morphing tran…
This paper addresses the facial biometric-enabled watchlist technology in which risk detectors are mandatory mechanisms for early detection of threats, as well as for avoiding offense to innocent travelers. We propose a multiparametric cost assessment and relative entropy measures as risk detectors. We experimentally demonstrate the effects of mis-identification and impersonation under various watchlist screening scenarios and constraints. The key contributions of this paper are the novel techniques for design and analysis of the biometric-enabled watchlist and the supporting infrastructure, a…
Purpose of the research: In the biometric community, visible human characteristics are popular and viable for verification and identification on mobile devices. However, imposters are able to spoof such characteristics by creating fake and artificial biometrics to fool the system. Visible biometric systems have suffered a high-security risk of presentation attack. Methods: In the meantime, challenge-based methods, in particular, gaze tracking and pupil dynamic appear to be more secure methods than others for contactless biometric systems. We review the existing work that explores gaze tracking…
Universidad Autonoma de Madrid（马德里自治大学）；European Commission - DG Joint Research Centre（欧洲委员会联合研究中心）；Hochschule Ansbach（安斯巴赫应用技术大学）
Iris recognition technology has attracted an increasing interest in the last decades in which we have witnessed a migration from research laboratories to real world applications. The deployment of this technology raises questions about the main vulnerabilities and security threats related to these systems. Among these threats presentation attacks stand out as some of the most relevant and studied. Presentation attacks can be defined as presentation of human characteristics or artifacts directly to the capture device of a biometric system trying to interfere its normal operation. In the case of…
Faculdade de Engenharia, Universidade Federal de Mato Grosso（马托格罗索联邦大学工程学院）
Advances in image processing and analysis as well as machine learning techniques have contributed to the use of biometric recognition systems in daily people tasks. These tasks range from simple access to mobile devices to tagging friends in photos shared on social networks and complex financial operations on self-service devices for banking transactions. In China, the use of these systems goes beyond personal use becoming a country's government policy with the objective of monitoring the behavior of its population. On July 05th 2021, the Brazilian government announced acquisition of a biometr…
As the Covid-19 pandemic grips the world, healthcare systems are being reshaped, where the e-health concepts become more likely to be accepted. Wearable devices often carry sensitive information from users which are exposed to security and privacy risks. Moreover, users have always had the concern of being counterfeited between the fabrication process and vendors' storage. Hence, not only securing personal data is becoming a crucial obligation, but also device verification is another challenge. To address biometrics authentication and physically unclonable functions (PUFs) need to be put in pl…
The vast progress in synthetic image synthesis enables the generation of facial images in high resolution and photorealism. In biometric applications, the main motivation for using synthetic data is to solve the shortage of publicly-available biometric data while reducing privacy risks when processing such sensitive information. These advantages are exploited in this work by simulating human face ageing with recent face age modification algorithms to generate mated samples, thereby studying the impact of ageing on the performance of an open-source biometric recognition system. Further, a real …
Blockchain has been emerging as a promising technology that could totally change the landscape of data security in the coming years, particularly for data access over Internet-of-Things and cloud servers. However, blockchain itself, though secured by its protocol, does not identify who owns the data and who uses the data. Other than simply encrypting data into keys, in this paper, we proposed a protocol called Biometric Blockchain (BBC) that explicitly incorporate the biometric cues of individuals to unambiguously identify the creators and users in a blockchain-based system, particularly to ad…
Biometric based authentication is currently playing an essential role over conventional authentication system; however, the risk of presentation attacks subsequently rising. Our research aims at identifying the areas where presentation attack can be prevented even though adequate biometric image samples of users are limited. Our work focusses on generating photorealistic synthetic images from the real image sets by implementing Deep Convolution Generative Adversarial Net (DCGAN). We have implemented the temporal and spatial augmentation during the fake image generation. Our work detects the pr…
With the rise and ever-increasing potential of deep learning techniques in recent years, publicly available medical datasets became a key factor to enable reproducible development of diagnostic algorithms in the medical domain. Medical data contains sensitive patient-related information and is therefore usually anonymized by removing patient identifiers, e.g., patient names before publication. To the best of our knowledge, we are the first to show that a well-trained deep learning system is able to recover the patient identity from chest X-ray data. We demonstrate this using the publicly avail…
Purpose: To create and evaluate the accuracy of an artificial intelligence Deep learning platform (ORAiCLE) capable of using only retinal fundus images to predict both an individuals overall 5 year cardiovascular risk (CVD) and the relative contribution of the component risk factors that comprise this risk. Methods: We used 165,907 retinal images from a database of 47,236 patient visits. Initially, each image was paired with biometric data age, ethnicity, sex, presence and duration of diabetes a HDL/LDL ratios as well as any CVD event wtihin 5 years of the retinal image acquisition. A risk sco…
R-FLoRA: Residual-Statistic-Gated Low-Rank Adaptation for Single-Image Face Morphing Attack Detection
SAFE Center, Department of Information Security and Communication Technology, Norwegian University of Science and Technology (NTNU)（安全中心，信息安全与通信技术系，挪威科学技术大学（NTNU））
