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In recent years, the interest in human authentication has been increasing. Biometrics are one of the easy authentication schemes, however, security and privacy problems limit their widespread usage. Following the interest in privacy protecting biometric authentication, template protection schemes for biometric modalities has increased significantly...
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... corresponds to a convolution in the spatial domain where every minutia is now represented by an isotropic two-dimensional Gaussian function with standard deviation σ C . Minutiae locations on a fingerprint image together with the Gaus- sian functions are illustrated in Figure 1. The minutiae orientation is incorporated into this representation by assigning each Gaussian a complex amplitude e jθi , where θ i is the ori- entation of the corresponding minutiae. ...
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Citations
... While it enhances template entropy, it may exhibit reduced performance compared to cancellable biometrics when adversaries present legitimate tokens. For instance, Hakan et al. applied bio-hashing with a fixed-length template generated through spectral minutiae representation, achieving an EER of 0% in FVC2002 databases, with the lowest EER in the stolen token scenario recorded at 14.77% (230). 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). ...
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.
... They demonstrated that the proposed fragile watermarking scheme can be applied to the integrity authentication systems based on biometric image. Also, [17] suggested a secure image encryption without size limitation using Arnold Transform and Random Strategies in order to alleviate the problem of security and inadequacy of Arnold Transform to handle images of any size. ...
... Disappearance of minutiae or appearance of new ones does not affect the size of the grid. Topcu et al. [17] applied biohashing to spectral minutiae as a form of template protection. Shao and Veldhuis [18] applied a HDS to spectral minutiae. ...
Storage of biometric data requires some form of template protection in order to preserve the privacy of people enrolled in a biometric database. One approach is to use a Helper Data System. Here it is necessary to transform the raw biometric measurement into a fixed-length representation. In this paper we extend the spectral function approach of Stanko and Skoric [WIFS2017], which provides such a fixed-length representation for fingerprints. First, we introduce a new spectral function that captures different information from the minutia orientations. It is complementary to the original spectral function, and we use both of them to extract information from a fingerprint image. Second, we construct a helper data system consisting of zero-leakage quantisation followed by the Code Offset Method. We show empirical data which demonstrates that applying our helper data system causes only a small performance penalty compared to fingerprint authentication based on the unprotected spectral functions.
... Once the existing transformed template is compromised, a new one can be re-issued as a replacement. Cancelable template ( [Savvides et al. 2004;Ratha et al. 2007; Ahmad et al. 2011]) and BioHashing ([Teoh et al. 2006;Topcu et al. 2013]) are the two most popular feature transformation-based methods. ...
As a promising bio-cryptographic technique, the fuzzy extractor seamlessly binds biometrics and cryptography for template protection and key generation. However, most existing methods hardly solve the following issues simultaneously: (1) Fingerprint registration, (2) Verification accuracy, (3) Security strength, and (4) Computational efficiency. In this article, we introduce a bio-crypto-oriented fingerprint verification scheme - Selective Vertex-indexed Triangulation (SViT) which maps minutia global topology to local triangulation with minimum information loss. Then, a SViT-based fuzzy extractor framework (FE-SViT) is proposed and high verification accuracy is achieved. The FE-SViT is highly parallelizable and efficient which makes it suitable for embedded devices.
... Over the last decade, a new innovative research field has emerged, called cancelable biometrics, aimed at finding algorithms dedicated to template protection. [1][2][3][4][5][6][7] The resulting systems must fulfill the following important properties: 8 i) non-invertibility, which refers to the difficulty in recovering the original biometric given the secure template; ii) revocability, which refers to the ability of generating a new template from the same biometric trait and iii) diversity, which is the difficulty in guessing one secure template given another secure template generated from the same biometric data. 9, 10 Many template protection schemes have been applied on the fingerprint. ...
In order to ensure privacy constraints in biometrics, new algorithms called template protection schemes have been proposed in the last ten years in the literature. Most of these algorithms require as input a feature having a fixed size. Texture features can be used within this context for fingerprints as the number of minutiae varies in general for different captures. BioHashing is a two authentication factor algorithm that can be used to enhance to ensure privacy while using biometrics. In this work, we compare different recent texture features from the literature within the BioHashing scheme while considering many constraints: efficiency, maximal representation size and constant size description. Experiments are conducted on three fingerprint databases from the FVC competition. Results permit us to conclude on the texture features to be used within this context.
Researchers and scholars from both communities, biometric and crypto, have proposed several template protection schemes over the years to secure biometric systems from vulnerabilities or attacks. In this paper, we present an improvement to a very popular biometric template protection technique known as Bio-hashing for fingerprint, which has a major drawback when the token or secret key gets stolen or compromised. Earlier, many researchers have proposed an improvement to this popular Bio-hashing technique. However, most of the research is focused on nonlinear transformations and using auxiliary data in the form of secret or key that needs to be stored in the database. Here our method uses modified Arnold’s cat map technique to introduce randomness in the orthogonalized tokenized (pseudo) random number during Bio-hashing phase. For this purpose, we calculate the statistical parameter from the enrolled biometric features in the form of mean (µ) and use this to form a seed/key for randomizing the orthogonalized pseudo-random number matrix. This key or seed needs not to be stored in the system or database which makes the technique more secure. Our system achieves an EER ~2.7% which is promising to consider the deliberate perturbations introduced in the FVC DB2 fingerprints.
Generation the Distance Matrix (DMx) is an important aspect that influences the correct solution of the routing problem in the dynamic variant. In the case of a frequent changing of points number and location, a continuous and effective update of the data is required, e.g., from more and more popular services such as Mapping APIs. The time-consuming nature of this process, which may extend the planning process, was emphasized. The article discusses the possibility of estimating the distance matrix based on the correction of the “haversine” distance. Method for the generation and updating of the DMx was proposed. The influence of update progress on some optimization algorithms was investigated. The research was carried out on the example of the real VRP problem. It was found that even a partial DMx update can significantly reduce the discrepancy between the VRP optimization results.
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Biometric systems are now proliferating in the very physical and informational fibres of our society, and with the usage of Biometric technology at widespread scale like AADHAAR India, the security risks it poses has gained wide attention as the pervasive hands of identity theft are spreading at an epidemic scale. To combat this, several biometric protection schemes have been proposed now and then. One of the most frequently applied techniques for identifying or authenticating individuals is the fingerprint recognition or authentication system. This survey focuses on the feature transformation schemes present at large in fingerprint and their comparative analysis describing strengths and weaknesses in terms of various performance metrics. Feature transformation methods make use of user-dependent invertible transform (F) or a transformation function (F′) that is non-invertible to transform acquired biometric characteristics from the registered or enrolled biometric sample. A summary of the key feature transformation schemes contained in the literature is discussed briefly in this survey.KeywordsFeature transformationTemplate protectionFingerprint securityBiometric security
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