A cancelable biometric authentication system based on feature-adaptive random projection
یک سیستم احراز هویت بیومتریک قابل لغو بر اساس طرح تصادفی سازگار با ویژگی-2021
Biometric template data protection is critical in preventing user privacy and identity from leakage. Random projection based cancelable biometrics is an efficient and effective technique to achieve biometric template protection. However, traditional random projection based cancelable template design suffers from the attack via record multiplicity (ARM), where an adversary obtains multiple transformed templates from different applica- tions and the associated parameter keys so as to assemble them into a full-rank linear equation system, thereby retrieving the original feature vector. To address this issue, in this paper we propose a feature-adaptive random projection based method, in which the projection matrixes, the key to the ARM, are generated from one basic matrix in conjunction with local feature slots. The generated projection matrixes are discarded after use, thus making it difficult for the adversary to launch the ARM. Moreover, the random projection in the proposed method is performed on a local-feature basis. This feature-adaptive random projection can mitigate the negative impact of biometric uncertainty on recognition accuracy, as it limits the error to part of the transformed feature vector rather than the entire vector. The proposed method is evaluated on four public available databases FVC2002 DB1-DB3 and FVC2004 DB2. The experimental results and security analysis show the validity of the proposed method.
Keywords: Biometric authentication | Template protection | Random projection | Cancelable biometrics
Design of a fingerprint template protection scheme using elliptical structures
طراحی طرح محافظت از اثر انگشت با استفاده از ساختارهای بیضوی-2021
Although biometric authentication is viewed as more prominent than password or token-based methodology in identity verification, biometric templates are vulnerable to attacks. This paper proposes a new approach for securing fingerprint templates using elliptical structures generated from the fingerprint minutiae. Authors generate a feature vector from the ellipse and will be projected onto a 3D-space to compute a binary string. The resultant binary string is transformed to frequency domain (DFT) and multiplied with a user specific random matrix to make it permanently non-invertible and secure. The results show the efficacy of the proposed method for protecting the fingerprints. c 2021 The Korean Institute of Communications and Information Sciences (KICS). Publishing services by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Keywords: Fingerprint | Ellipse | Discrete Fourier transform | Template protection
BIOFUSE: A framework for multi-biometric fusion on biocryptosystem level
BIOFUSE: چارچوبی برای همجوشی چند بیومتریک در سطح بیو کریپتوسیستم-2021
Biometric cryptosystems or biocryptoystems are gaining prominence for cryptographic key generation, encryption and biometric template protection. However, the most popular state-of-the-art biocryptosystems- fuzzy commitment and fuzzy vault are prone to multiple security attacks. Recently proposed multi-biometric cryptosystems improve security and enhance recognition performance. They perform the fusion of multi-biometric characteristics with either a single biocryptosystem or independently accessed, multiple biocryptosystems. An attack on any of the involved biocryptosystems can weaken the security of the whole system. In our paper, we propose a multi-biometric fusion framework- BIOFUSE, that combines fuzzy commitment and fuzzy vault using the format-preserving encryption scheme. BIOFUSE makes it improbable for an attacker to get unauthorized access to the system without impersonation of all the biometric inputs of the genuine user at the same instant. We present 4 most basic ways of constructing BIOFUSE and found only 1 named S- BIOFUSE (S3) as a secure design. We compare the recognition performance of the proposed scheme with existing multi-biometric cryptosystems on various databases. The results show 0:98 true match rate at 0:01 false match rate on a virtual IITD-DB1 database that indicates that our proposed work achieves significantly good recognition performance while providing high security.© 2020 Elsevier Inc. All rights reserved.
Keywords: Biometric cryptosystem | Biometric template protection | Multi-biometric fusion | Fuzzy commitment | Fuzzy vault | Format-preserving encryption
Alignment-free cancelable fingerprint templates with dual protection
الگوهای اثر انگشت قابل انعطاف بدون تراز با محافظت دوگانه-2021
Cancelable ﬁngerprint templates Discrete wavelet transform Attacks via record multiplicity Cancelable biometrics is an important biometric template protection technique. However, many existing cancelable ﬁngerprint templates suffer post-transformation performance deterioration and the attacks via record multiplicity (ARM). In this paper, we design alignment-free cancelable ﬁngerprint templates with dual protection, which is composed of the window-shift-XOR model and the partial discrete wavelet transform. The former defuses the ARM threat and is combined with the latter to provide dual protection and enhance matching performance. The designed cancelable templates meet the requirements of non-invertibility, diversity and revocability and demonstrate superior recognition accuracy, when evaluated over public databases; for example, the Equal Error Rate of the proposed method in the lost-key scenario under the 1vs1 protocol is 0% for both FVC2002 DB1 and DB2, 1.63% for FVC2002 DB3, 7.35% for FVC2004 DB1 and 4.69% for FVC2004DB2.© 2020 Elsevier Ltd. All rights reserved.
Keywords: Cancelable biometrics | Alignment-free | Cancelable fingerprint templates | Discrete wavelet transform | Attacks via record multiplicity
Design of cancelable MCC-based fingerprint templates using Dyno-key model
طراحی الگوهای اثر انگشت مبتنی بر MCC قابل لغو با استفاده از مدل Dyno-key-2021
Minutia Cylinder Code (MCC) is an effective, high-quality representation of local minutia structures. MCC templates demonstrate fast and excellent ﬁngerprint matching performance, but if compromised, they can be reverse-engineered to retrieve minutia information. In this paper, we propose alignment-free cancelable MCC-based templates by exploiting the MCC feature extraction and representation. The core component of our design is a dynamic random key model, called Dyno-key model. The Dyno-key model dynamically extracts elements from MCC’s binary feature vectors based on randomly generated keys. Those extracted elements are discarded after the block-based logic operations so as to increase security. Leveling with the performance of the unprotected, reproduced MCC templates, the proposed method exhibits competitive performance in comparison with state-of-the-art cancelable ﬁngerprint templates, as evaluated over seven public databases, FVC2002 DB1-DB3, FVC2004 DB1 and DB2, and FVC2006 DB2 and DB3. The proposed cancelable MCC-based templates satisfy all the requirements of biometric template protection.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Cancelable biometrics | Minutia cylinder code | Cancelable fingerprint templates | Biometric template protection | Alignment-free
Secure and verifiable iris authentication system using fully homomorphic encryption
سیستم تأیید هویت عنبیه امن و قابل تأیید با استفاده از رمزگذاری کاملاً همگون-2021
With the escalated usage of a biometric authentication system (BAS), template protection for biometrics attracted research interest in recent years. The assumption behind the existing homomorphic encryption-based BASs is that the server performs the computations honestly. In a malicious server setting, the server may return an arbitrary result to save the computational resources, which may result in false accept/reject. To tackle this challenge, we propose a secure and verifiable classification based iris authentication system (SvaS). SvaS aims to achieve both privacy-preserving (PP) training and PP classification of Nearest Neighbor and Multi-class Perceptron models. The Fan-vercauteren scheme provides confidentiality for the iris templates, and aggregate verification vector helps to verify the correctness of the computed classification result. Extensive experimental results on benchmark iris databases demonstrate that SvaS provides privacy to the iris templates with no loss in accuracy and eliminates the need to trust the server.
Keywords: Biometrics | Privacy-preserving | Homomorphic encryption | Multi-class Perceptron | Nearest Neighbor
A Tokenless Cancellable Scheme for Multimodal Biometric Systems
طرح غیر قابل لغو برای سیستم های بیومتریک چند حالته-2021
Biometric template protection (BTP) is an open problem for biometric identity management systems. Cancellable biometrics is commonly designed to protect biometric templates with two input factors i.e., biometrics and a token used in template replacement. However, the token is often required to be kept secretly; otherwise, the protected template could be vulnerable to several security attacks and breaches of privacy. In this paper, we propose a tokenless cancellable biometrics scheme called Multimodal Extended Feature Vector (M•EFV) Hashing that employs an improved XOR encryption/decryption notion to operate on the transformation key. We stress on multimodal biometrics where the real-valued face and fingerprint vectors are fused and embedded into a binarized cancellable template. Specifically, M•EFV hashing consists of three stages of transformation: 1) normalization and bio- metric fusion; 2) randomization and binarization; and 3) cancellable template generation. To evaluate the proposed scheme, several benchmarking datasets, i.e., FVC2002, FVC2004 for fingerprint and LFW for face are used in experiments. The verification performance is vali- dated by employing the FVC matching protocol. Various attacks are simulated and analysed in the worst-case scenario. Lastly, unlinkability and revocability properties are examined experimentally.© 2021 Elsevier Ltd. All rights reserved.
Keywords: Feature-level Fusion | Multimodal Biometrics | Tokenless Cancellable Biometrics | Privacy and security | XOR encryption/decryption
Providing robust security measures to Bloom filter based biometric template protection schemes
ارائه اقدامات امنیتی قوی برای طرح های حفاظت از قالب های بیومتریک بر اساس فیلتر بلوم-2017
Template protection is an essential requirement of biometric recognition systems. These special methods are designed to provide the necessary security and privacy privileges to the registered users of the biometric system. Similar to other security domains, these schemes require to follow certain properties or characteristics like unlinkability, irreversibility and low information leakage from the stored data. Ideally, these schemes must not result in any degradation of the biometric recognition performance as a whole. Designing a system which balances all these factors efficiently has been a major challenge. Contemporary frame works generally relax one or more of these parameters in order to achieve their application specific goals. However recently, a modified Bloom filter based scheme was proposed which apparently provided competent security measures in addition to high recognition accu racy rates. However subsequent studies refuted the security guarantees of the scheme by providing adversarial attacks with practical bounds. In our work, we address this issue and propose a modified Bloom filter based framework which provides all the desirable security measures of a biometric template protection scheme. Not only have we theoretically proved all the security notions of our model, but also experimentally verified our claims. Thus our proposed design provides satisfactory security guarantees in addition to the implicit ad vantages of using Bloom filters like speed and efficiency. Finally, there is no reduction in the performance rates of the underlying system since we perform the matching of the bio metric traits in their original forms (in contrast to some transformed space).
Keywords: Biometrics | Iris | Security | Bloom filters | Perfect secrecy
Security analysis and improvement of some biometric protected templates based on Bloom filters
تجزیه و تحلیل امنیت و بهبود برخی از الگوهای محافظت بیومتریک بر اساس فیلترهای بلوم-2017
In this work, we develop an unlinkability and irreversibility analysis of the so-called Bloom filter-based iris biometric template protection introduced at ICB 2013. We go further than the unlinkability analysis of Hermans et al. presented at BIOSIG 2014. Firstly we analyse unlinkability on protected templates built from two different iriscodes coming from the same iris whereas Hermans et al. analysed only protected templates from the same iriscode. Moreover we introduce an irreversibility analysis that exploits non-uniformity of the biometric data. Our experiments demonstrate new vulnerabilities of this scheme. Then we will discuss the security of other similar protected biometric templates based on Blooms filters that have been suggested in the literature since 2013. Finally we suggest a Secure Multiparty Computation (SMC) protocol, that benefits of the alignment-free feature of this Bloom filter construction, in order to compute efficiently and securely the matching scores.
Keywords:Bloom filter | Biometric security