Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> We combine well-known techniques from the areas of error-correcting codes and cryptography to achieve a new type of cryptographic primitive that we refer to as a fuzzy commitment scheme. Like a conventional cryptographic commitment scheme, our fuzzy commitment scheme is both concealing and binding : it is infeasible for an attacker to learn the committed value, and also for the committer to decommit a value in more than one way. In a conventional scheme, a commitment must be opened using a unique witness , which acts, essentially, as a decryption key. By contrast, our scheme is fuzzy in the sense that it accepts a witness that is close to the original encrypting witness in a suitable metric, but not necessarily identical. This characteristic of our fuzzy commitment scheme makes it useful for applications such as biometric authentication systems, in which data is subject to random noise. Because the scheme is tolerant of error, it is capable of protecting biometric data just as conventional cryptographic techniques, like hash functions, are used to protect alphanumeric passwords. This addresses a major outstanding problem in the theory of biometric authentication. We prove the security characteristics of our fuzzy commitment scheme relative to the properties of an underlying cryptographic hash function. <s> BIB001 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> We provide formal definitions and efficient secure techniques for ::: ::: ::: turning biometric information into keys usable for any cryptographic application, and ::: ::: ::: reliably and securely authenticating biometric data. <s> BIB002 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Biometrics-based user authentication has several advantages over traditional password-based systems for standalone authentication applications, such as secure cellular phone access. This is also true for new authentication architectures known as crypto-biometric systems, where cryptography and biometrics are merged to achieve high security and user convenience at the same time. In this paper, we explore the realization of a previously proposed cryptographic construct, called fuzzy vault, with the fingerprint minutiae data. This construct aims to secure critical data (e.g., secret encryption key) with the fingerprint data in a way that only the authorized user can access the secret by providing the valid fingerprint. The results show that 128-bit AES keys can be secured with fingerprint minutiae data using the proposed system. <s> BIB003 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Reliable information security mechanisms are required to combat the rising magnitude of identity theft in our society. While cryptography is a powerful tool to achieve information security, one of the main challenges in cryptosystems is to maintain the secrecy of the cryptographic keys. Though biometric authentication can be used to ensure that only the legitimate user has access to the secret keys, a biometric system itself is vulnerable to a number of threats. A critical issue in biometric systems is to protect the template of a user which is typically stored in a database or a smart card. The fuzzy vault construct is a biometric cryptosystem that secures both the secret key and the biometric template by binding them within a cryptographic framework. We present a fully automatic implementation of the fuzzy vault scheme based on fingerprint minutiae. Since the fuzzy vault stores only a transformed version of the template, aligning the query fingerprint with the template is a challenging task. We extract high curvature points derived from the fingerprint orientation field and use them as helper data to align the template and query minutiae. The helper data itself do not leak any information about the minutiae template, yet contain sufficient information to align the template and query fingerprints accurately. Further, we apply a minutiae matcher during decoding to account for nonlinear distortion and this leads to significant improvement in the genuine accept rate. We demonstrate the performance of the vault implementation on two different fingerprint databases. We also show that performance improvement can be achieved by using multiple fingerprint impressions during enrollment and verification. <s> BIB004 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> We propose an authentication scheme using fingerprint biometrics, protected by a construct called a Fuzzy Extractor. We look at a new way of quantizing and digitally representing the minutiae measurements so that a construct called PinSketch can be applied to the minutiae. This is converted to a Fuzzy Extractor by tying some random information to the minutiae measurements. We run a matching algorithm at chosen quantization parameters and show that the authentication accuracy is within acceptable limits. We demonstrate that our authentication system succeeds in protecting the users' identity. <s> BIB005 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Fuzzy vault is a practical and promising scheme, which can protect biometric templates and perform secure key management simultaneously. Alignment of the template biometric sample and the query one in the encrypted domain remains a challenging task. While implementing fuzzy fingerprint vault, the accuracy of alignment in encrypted domain cannot be ensured and the information leakage may be caused because of the alignment. In this paper, an alignment-free fingerprint cryptosystem based on fuzzy vault scheme is developed fusing the local features, known minutia descriptor and minutia local structure, which are invariant to the transformation in fingerprint capturing. Three fusion strategies are employed to integrate the two local features. Huffman coding technology is used to compress the storage volume of the minutia descriptor vault. The proposed fingerprint cryptosystem can avoid the alignment procedure and improve the performance and security of the fuzzy vault scheme at the same time. Experiments on FVC2002-DB2a and FVC2002-DB1a are conducted to show the promising performance of the proposed fingerprint cryptosystem. Security level of proposed cryptosystem will not decrease and even rise in some circumstances. The best trade-off results obtained is GAR=92%(FAR=0), under the 53-bit security. Despite the larger template storage expense, the proposed alignment-free fingerprint cryptosystem outperforms the minutiae-based fingerprint cryptosystems with alignment in the terms of accuracy and security. <s> BIB006 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> In this paper, we introduce the Minutia Cylinder-Code (MCC): a novel representation based on 3D data structures (called cylinders), built from minutiae distances and angles. The cylinders can be created starting from a subset of the mandatory features (minutiae position and direction) defined by standards like ISO/IEC 19794-2 (2005). Thanks to the cylinder invariance, fixed-length, and bit-oriented coding, some simple but very effective metrics can be defined to compute local similarities and to consolidate them into a global score. Extensive experiments over FVC2006 databases prove the superiority of MCC with respect to three well-known techniques and demonstrate the feasibility of obtaining a very effective (and interoperable) fingerprint recognition implementation for light architectures. <s> BIB007 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> The core of bio-cryptography lies in the stability of cryptographic keys generated from uncertain biometrics. It is essential to minimize every possible uncertainty during the biometric feature extraction process. In fingerprint feature extraction, it is perceived that pixel-level image rotation transformation is a lossless transformation process. In this paper, an investigation has been conducted on analyzing the underlying mechanisms of fingerprint image rotation processing and potential effect on the major features, mainly minutiae and singular point, of the rotation transformed fingerprint. Qualitative and quantitative analyses have been provided based on intensive experiments. It is observed that the information integrity of the original fingerprint image can be significantly compromised by image rotation transformation process, which can cause noticeable singular point change and produce a non-negligible number of fake minutiae. It is found that the quantization and interpolation process can change the fingerprint features significantly without affecting the visual image. Experiments show that up to 7% bio-cryptographic key bits can be affected due to this rotation transformation. <s> BIB008 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Biometric techniques provide a feasible solution for protecting personal information at a high security level. However, biometric features themselves demand protection. As a promising method, fuzzy extractor seamlessly binds a cryptographic key to biometric features, in order to prevent both keys and features being exposed to attackers. Some related research has been done in this area however three major issues are still unsolved, which are : 1) Feature alignment 2) Verification accuracy. 3) Information leakage. In this paper, an alignment-free fingerprint fuzzy extraction scheme is proposed. To eliminate the alignment process, we use the minutia local structure features which has been proved to be stable, discriminative, rotation and shift free. The Dual Layer Structure Check (DLSC) verification scheme is base on the minutia local structure and it achieves a high verification performance. In this paper, we proposed a near-equivalent version of DLSC (NeDLSC) that can be directly employed by the existing bio-cryptographic constructions. Then a new fuzzy extractor scheme which is on the basis of NeDLSC is demonstrated. The preliminary experiments on publicly-available database FVC2002 shows a high verification accuracy. <s> BIB009 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Due to the popularity of biometric authentication system, it is extremely important to protect the biometric template available in the networks. Template protection technique is a critical issue in biometric authentication system. Basically the protection technique can be categorized into Biometric CryptoSystem(BCS) and Cancelable Biometrics(CB). In this paper, an efficient hybrid template protection technique which combines both Biometric CryptoSystem(BCS) and Cancelable Biometrics(CB) was proposed. The proposed system, uses key generating cryptosystem and feature transformation method. The limtation of the feature transform was overcomed by this approach. We focus on these techniques using Iris, Fingerprint (i.e. multimodal Biometrics)as traits. The Experimental Results shows no degradation in results by combining both the Biometric CryptoSystem(BCS) and Cancelable Biometrics(CB). It is important that the biometric authentication sysem should withstand the attacks and the template theft by the adversary. <s> BIB010 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Lack of the capability of cancellability in a biometric cryptosystem makes it impossible to be deployed broadly in real applications. This is because the compromise of a template in one application often means its loss in all other applications. To solve this problem, we equip a minutiae-based fuzzy vault with cancellability by applying a polar transformation to each Delaunay triangle group so as to enhance the security level of the biometric template. The unit of the non-invertible polar transformation is a triangle as a whole instead of a single minutiae point which makes the proposed method to be more stable and insensitive to non-linear distortion. Experimental results on public fingerprint databases FVC2002 DB1 and DB2 demonstrate the valid of the proposed method. <s> BIB011 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors. <s> BIB012 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Abstract Fingerprint is a highly discriminative biometric modality and has gained a lot of interest in both forensic and civil applications. However, it is well known that fingerprint template stored in plaintext is vulnerable to attack. A secure fingerprint template has to be both non-invertible and non-linkable. Minutia cylinder-code (MCC) is a fixed-length and highly discriminative type of minutia descriptor. However, most of the current MCC based fingerprint matching algorithms do not possess the non-linkable property. In this paper, a secured fingerprint MCC matching scheme is proposed by utilizing l 1 -minimization, where the enrolled fingerprint MCC template is stored in cyphertext form (i.e., E-MCC) and is recognizable only when a close enough query fingerprint presented to the system. Our experimental results on FVC2002 DB1, FVC2002 DB2 and FVC2004 DB1 databases show that the proposed system is highly secure and accurate. The GAR with FAR = 0 on FVC2002 DB1, FVC2002 DB2 and FVC2004 DB1 are 91.4%, 84.0% and 65.6%, respectively, with a security level of 33 bits. The performance of the proposed encrypted domain matching algorithm outperforms state-of-the-art fingerprint encryption algorithms. <s> BIB013 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> Abstract Biometric based authentication systems have been widely deployed to mobile devices. Security and privacy issues arise especially when the biometric templates stored in centralized database or personal portable devices are obtained by adversaries. To make matters worse, unlike password, biometric traits are irreplaceable once compromised. Despite the fact that a number of methods have been reported to protect biometric templates, there are rare solutions that satisfy all the criteria of template protection simultaneously (i.e. non-linkability, cancelability, non-invertibility and performance). In this paper, we propose an alignment-free cancelable template scheme to protect fingerprint minutiae. The proposed template scheme is the extended version of the polar grid based 3-tuple quantization with condensed feature length for lower computation cost. To enhance the non-invertibility, bit-toggling strategy is proposed to inject noise into the proposed fingerprint template. Furthermore, cancelability is also achieved by incorporating discrete Fourier transform and random projection on the proposed template. Due to the use of discrete Fourier transform, the resultant template will be converted into complex form which increases the difficulty of attacker in breaking its security. The proposed template scheme is evaluated on FVC2002 and FVC2004 databases (DB1, DB2 and DB3) and the experimental results demonstrate a comparable accuracy over the existing methods. The observation from the security and privacy analysis suggests that the proposed template is robust against the major attacks, e.g. template inversion attack, attack via record multiplicity, etc. Lastly, we demonstrate that the proposed template can be applied in the bio-cryptosystems. <s> BIB014 </s> Security and Accuracy of Fingerprint-Based Biometrics: A Review <s> Biometric Cryptosystems <s> An Outsized keys of various sizes such as 256,192 or 128 binary digits are being used for the existing symmetric cryptographic algorithms. These long keys are very tough to recollect. Consequently, key is deposited in a plastic card with a built-in microprocessor, tokens which cannot be tampered. Also an authentication based on password can be used to restrict the access of key related to cryptography. But there is every chance that these user nominated passwords can be lost, taken or predicted by dictionary attacks. Moreover, in symmetric cryptography there is another probable risk of safety that is copy of same secret key exists with receiver and sender and this must be kept secret. Probable solution to above deliberated key management problem is by using biological data of both receiver and sender in all sessions of communication. One of the foremost problem with biometrics is that once it gets negotiated it can't be reused. For cancelling and reissuing biometrics template, cancelable biometrics has been anticipated so that the above mentioned problem may be overcome. A method to generate 128 bit symmetric key using cancelable fingerprint template of receiver and sender is being proposed in this current work. This present approach confirms the privacy of fingerprints by one way transformation of original template into cancelable one as well as resolves the difficulty of key storage and key distribution. The reason is that in this approach the key is neither deposited in any location nor it is sent to the receiver. <s> BIB015
A biometric cryptosystem combines biometrics with a cryptographic key and merges the advantages of both biometrics and cryptosystems. Different to a cancelable biometric system, which can only provide a match or non-match report, a biometric cryptosystem can output a key by either binding it with the biometric features, such as fuzzy commitment (FC) BIB001 and fuzzy vault (FV)   , or directly generating the key from the biometric features, for example, fuzzy extractor (FE) BIB002 . Teoh and Kim  utilized the fuzzy commitment scheme to protect fingerprint features. Since it is convenient to have biometric features in the binary format, the authors processed the features with a randomized dynamic quantization transformation. However, in most cases of fingerprint minutiae matching, the extracted minutia set is a point set and is unordered. To protect the fingerprint minutia data in the point set, Uludag et al. BIB003 applied the original concept of fuzzy vault to the fingerprint minutia data. In this method, a 128-bit cryptographic key is feasibly bound with the fingerprint minutia data, but this method requires image alignment. Later, Nandakumar et al. BIB004 introduced a fingerprint minutiae based fuzzy vault scheme and utilized the high curvature points to assist image alignment, thus making alignment more accurate without leaking any orientation information or minutia position within the template data. All the above-mentioned approaches require pre-alignment (i.e., registration) to rotate and translate the query image with respect to the template image. However, the pre-alignment process may cause non-negligible noise (e.g., generating fake minutiae and altering the singular point position), as investigated by Zhang et al. BIB008 . Alignment-free approaches that require no image pre-alignment can avoid the above shortcomings. Li et al. BIB006 proposed a fuzzy vault scheme, which combines two local structures, the minutiae descriptor and minutia local structure. By using three fusion approaches, the two transformation-invariant local structures are integrated in the proposed scheme. Unlike the schemes of fuzzy commitment and fuzzy vault discussed earlier, which are key binding schemes, fuzzy extractors are key generation schemes based on the concept introduced in BIB002 . Arakala et al. BIB005 implemented the fuzzy extractor in minutiae-based fingerprint authentication. Given a fingerprint minutia set, all the minutiae are quantized and represented by a set of binary strings, which are subsequently input into an existing secure sketch, named PinSketch. Xi et al. BIB009 proposed a fuzzy extractor using a dual-layer local structure. In this system, rotation-and transformation-free dual-layer structures are developed to guard biometric templates against attacks. Later, some other fuzzy extractor systems BIB010  were also proposed with enhanced performance. Liu and Zhao BIB013 utilized l 1 -minimization to secure the fingerprint templates and store them in cyphertext form. Fingerprint matching is carried out in the encrypted domain and authentication is successful only when the query fingerprint is close enough to the template fingerprint. As the template is generated from the Minutia Cylinder-Code (MCC) BIB007 with the proper design of the secure algorithm, the proposed system achieves high security and recognition accuracy. Given the fact that conventional biometric cryptosystems are not equipped with revocability, recently, the cancelable technique is employed to enhance the security of biometric cryptosystem. Yang et al. BIB011 proposed a cancelable fuzzy vault system to encrypt the Delaunay triangle group based fingerprint features. The cancelable transformation is derived from the polar transformation. The transformation unit in this work is a triangle instead of a single minutia, which enables the system to be less sensitive to biometric uncertainty. Alam et al. BIB014 put forward a biometric cryptosystem, which incorporates the discrete Fourier transform (DFT) and random projection based cancelable technique to heighten security. In the proposed system, polar grid based fingerprint features are transformed by using the DFT and random projection, creating a non-invertible template. Also, a bit-toggling strategy is utilized to inject noise into the generated template, so as to further strengthen template security. Sarkar and Singh BIB015 proposed generation of cryptographic keys from cancelable fingerprint templates. Different keys with a length of 128 bits can be generated by cancelling and reissuing different fingerprint templates. This reduces the potential risk that the same secret key that existed with the receiver and sender could be leaked after negotiation. In this section, detailed analysis and discussion about biometric cryptosystems are given, from the initial concepts, e.g., fuzzy commitment BIB001 , fuzzy vault  , and fuzzy extractor BIB002 , to various complex algorithms derived afterwards BIB006 BIB005 BIB009 BIB010  . One of the advantages of biometric cryptosystems is that they can bind or directly generate a cryptographic key, which can be used for both authentication and data encryption. However, most biometric cryptosystems are not equipped with cancelability. Some researchers realized this problem and thus developed biometric cryptosystems with revocability BIB014 BIB015 , so as to enhance system security. It is worth noting that nowadays deep learning techniques BIB012 have been involved in more and more biometric applications, e.g., face and voice recognition, but there is almost no research regarding the security of deep learning based biometrics. Therefore, more research effort should be devoted to this direction. A comparison of all the above fingerprint template protection approaches, whether it be cancelable biometrics or biometric cryptosystems, are reported in Tables 3 and 4 , respectively. Randomized dynamic quantization, transformation to binarized biometric data, and protection by using fuzzy commitment 