A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Details multimodal biometrics and its exceptional utility for increasingly reliable human recognition systems. Reveals the substantial advantages of multimodal systems over conventional identification methods. <s> BIB001 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <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. Our techniques apply not just to biometric information, but to any keying material that, unlike traditional cryptographic keys, is (1) not reproducible precisely and (2) not distributed uniformly. We propose two primitives: a fuzzy extractor extracts nearly uniform randomness R from its biometric input; the extraction is error-tolerant in the sense that R will be the same even if the input changes, as long as it remains reasonably close to the original. Thus, R can be used as a key in any cryptographic application. A secure sketch produces public information about its biometric input w that does not reveal w, and yet allows exact recovery of w given another value that is close to w. Thus, it can be used to reliably reproduce error-prone biometric inputs without incurring the security risk inherent in storing them. In addition to formally introducing our new primitives, we provide nearly optimal constructions of both primitives for various measures of closeness of input data, such as Hamming distance, edit distance, and set difference. <s> BIB002 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> In this paper, we propose a feature-level fusion approach for improving the efficiency of palmprint identification. Multiple elliptical Gabor filters with different orientations are employed to extract the phase information on a palmprint image, which is then merged according to a fusion rule to produce a single feature called the Fusion Code. The similarity of two Fusion Codes is measured by their normalized hamming distance. A dynamic threshold is used for the final decisions. A database containing 9599 palmprint images from 488 different palms is used to validate the performance of the proposed method. Comparing our previous non-fusion approach and the proposed method, improvement in verification and identification are ensured. <s> BIB003 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> We propose the first practical and secure way to integrate the iris biometric into cryptographic applications. A repeatable binary string, which we call a biometric key, is generated reliably from genuine iris codes. A well-known difficulty has been how to cope with the 10 to 20 percent of error bits within an iris code and derive an error-free key. To solve this problem, we carefully studied the error patterns within iris codes and devised a two-layer error correction technique that combines Hadamard and Reed-Solomon codes. The key is generated from a subject's iris image with the aid of auxiliary error-correction data, which do not reveal the key and can be saved in a tamper-resistant token, such as a smart card. The reproduction of the key depends on two factors: the iris biometric and the token. The attacker has to procure both of them to compromise the key. We evaluated our technique using iris samples from 70 different eyes, with 10 samples from each eye. We found that an error-free key can be reproduced reliably from genuine iris codes with a 99.5 percent success rate. We can generate up to 140 bits of biometric key, more than enough for 128-bit AES. The extraction of a repeatable binary string from biometrics opens new possible applications, where a strong binding is required between a person and cryptographic operations. For example, it is possible to identify individuals without maintaining a central database of biometric templates, to which privacy objections-might be raised <s> BIB004 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> The popularity of biometrics and its widespread use introduces privacy risks. To mitigate these risks, solutions such as the helper-data system, fuzzy vault, fuzzy extractors, and cancelable biometrics were introduced, also known as the field of template protection. In parallel to these developments, fusion of multiple sources of biometric information have shown to improve the verification performance of the biometric system. In this work we analyze fusion of the protected template from two 3D recognition algorithms (multi-algorithm fusion) at feature-, score-, and decision-level. We show that fusion can be applied at the known fusion-levels with the template protection technique known as the Helper-Data System. We also illustrate the required changes of the Helper-Data System and its corresponding limitations. Furthermore, our experimental results, based on 3D face range images of the FRGC v2 dataset, show that indeed fusion improves the verification performance. <s> BIB005 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Pervasive computing environments present unique challenges related to specific aspects of security and multimodality (SMPE). In fact, the accessibility of such an environment can be certainly improved using natural interfaces and multimodal interaction systems, which offer users the freedom to select one of multiple modes of interaction with services. They also offer users the opportunity to break through barriers on human–computer interaction making communication intuitive and spontaneous. On the other hand, while extending and facilitating the ways of accessing the environment, security threads arise and the environment must be properly instrumented in order to protect itself from malicious attacks and/or from erroneous actions performed by non-expert users. We received eighteen manuscripts. After the pre-review process, fourteen manuscripts were selected for the first review. Eight manuscripts were finally selected for this Special Issue after the first, second, and third review processes. Each manuscript selected from the pre-review was blindly reviewed by at least three reviewers consisting of guest editors and external reviewers. <s> BIB006 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Form a privacy perspective most concerns against the common use of biometrics arise from the storage and misuse of biometric data. Biometric cryptosystems and cancelable biometrics represent emerging technologies of biometric template protection addressing these concerns and improving public confidence and acceptance of biometrics. In addition, biometric cryptosystems provide mechanisms for biometric-dependent key-release. In the last years a significant amount of approaches to both technologies have been published. A comprehensive survey of biometric cryptosystems and cancelable biometrics is presented. State-of-the-art approaches are reviewed based on which an in-depth discussion and an outlook to future prospects are given. <s> BIB007 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Fuzzy commitment schemes have been established as a reliable means of binding cryptographic keys to binary feature vectors extracted from diverse biometric modalities. In addition, attempts have been made to extend fuzzy commitment schemes to incorporate multiple biometric feature vectors. Within these schemes potential improvements through feature level fusion are commonly neglected. In this paper a feature level fusion technique for fuzzy commitment schemes is presented. The proposed reliability-balanced feature level fusion is designed to re-arrange and combine two binary biometric templates in a way that error correction capacities are exploited more effectively within a fuzzy commitment scheme yielding improvement with respect to key-retrieval rates. In experiments, which are carried out on iris-biometric data, reliability-balanced feature level fusion significantly outperforms conventional approaches to multi-biometric fuzzy commitment schemes confirming the soundness of the proposed technique. <s> BIB008 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Multibiometric systems are being increasingly de- ployed in many large-scale biometric applications (e.g., FBI-IAFIS, UIDAI system in India) because they have several advantages such as lower error rates and larger population coverage compared to unibiometric systems. However, multibiometric systems require storage of multiple biometric templates (e.g., fingerprint, iris, and face) for each user, which results in increased risk to user privacy and system security. One method to protect individual templates is to store only the secure sketch generated from the corresponding template using a biometric cryptosystem. This requires storage of multiple sketches. In this paper, we propose a feature-level fusion framework to simultaneously protect multiple templates of a user as a single secure sketch. Our main contributions include: (1) practical implementation of the proposed feature-level fusion framework using two well-known biometric cryptosystems, namery,fuzzy vault and fuzzy commitment, and (2) detailed analysis of the trade-off between matching accuracy and security in the proposed multibiometric cryptosystems based on two different databases (one real and one virtual multimodal database), each containing the three most popular biometric modalities, namely, fingerprint, iris, and face. Experimental results show that both the multibiometric cryptosystems proposed here have higher security and matching performance compared to their unibiometric counterparts. <s> BIB009 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> In this correspondence, we analyze the vulnerabilities of biometric authentication protocols with respect to user and data privacy. The goal of an adversary in such context is not to bypass the authentication but to learn information either on biometric data or on users that are in the system. We elaborate our analysis on a general system model involving four logical entities (sensor, server, database, and matcher), and we focus on internal adversaries to encompass the situation where one or a combination of these entities would be malicious. Our goal is to emphasize that when going beyond the usual honest-but-curious assumption much more complex attacks can affect the privacy of data and users. On the one hand, we introduce a new comprehensive framework that encompasses the various schemes we want to look at. It presents a system model in which each internal entity or combination of entities is a potential attacker. Different attack goals are considered and resulting requirements on data flows are discussed. On the other hand, we develop different generic attacks. We follow a blackbox approach in which we consider components that perform operations on biometric data but where only the input/output behavior is analyzed. These attack strategies are exhibited on recent schemes such as the distributed protocol of Bringer (ACISP 2007), which is based on the Goldwasser-Micali cryptosystem, the related protocol of Barbosa (ACISP 2008), which uses the Paillier cryptosystem, and the scheme of Stoianov (SPIE 2010), that features the Blum-Goldwasser cryptosystem. All these schemes have been developed in the honest-but-curious adversary model and show potential weaknesses when considered in our malicious insider attack model. <s> BIB010 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Recognizing people by their ear has recently received significant attention in the literature. Several reasons account for this trend: first, ear recognition does not suffer from some problems associated with other non-contact biometrics, such as face recognition; second, it is the most promising candidate for combination with the face in the context of multi-pose face recognition; and third, the ear can be used for human recognition in surveillance videos where the face may be occluded completely or in part. Further, the ear appears to degrade little with age. Even though current ear detection and recognition systems have reached a certain level of maturity, their success is limited to controlled indoor conditions. In addition to variation in illumination, other open research problems include hair occlusion, earprint forensics, ear symmetry, ear classification, and ear individuality. This article provides a detailed survey of research conducted in ear detection and recognition. It provides an up-to-date review of the existing literature revealing the current state-of-art for not only those who are working in this area but also for those who might exploit this new approach. Furthermore, it offers insights into some unsolved ear recognition problems as well as ear databases available for researchers. <s> BIB011 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> Evidence of identity (EOI), sometimes mentioned as breeder documents in a physical representation form, refers to a single or a set of evidence that can be used to provide confidence to the claimed identity. Trust of evidence of identity needs prudential assessment by an authority or a service provider before such evidence of identity can be accepted for identity verification or eligibility evaluation purposes. This is especially the case when such purposes have a high risk of cost, security, and other critical consequences. In this paper we analyze the status of deployed EOIs in the scope of ePassport issuance; and then attempt to define the implementation types, fraud scenarios, security objectives, and trust levels for EOIs, which have not been clearly defined in existing research and standardization societies. As a pilot survey work in this field, recommendations from policy and technology perspectives towards a highly-trusted EOI framework for standardization are shaped towards future ePassport issuance standardization and practice. Finally, a new design of birth certificate, compliant to the proposed recommendations, is presented as an example of trusted EOI. <s> BIB012 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> This chapter presents a system which simultaneously acquires face and iris samples using a single sensor, with the goal of improving recognition accuracy while minimizing sensor cost and acquisition time. The resulting system improves recognition rates beyond the observed recognition rates for either isolated biometrics. <s> BIB013 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Introduction <s> The iris and face are among the most promising biometric traits that can accurately identify a person because their unique textures can be swiftly extracted during the recognition process. However, unimodal biometrics have limited usage since no single biometric is sufficiently robust and accurate in real-world applications. Iris and face biometric authentication often deals with non-ideal scenarios such as off-angles, reflections, expression changes, variations in posing, or blurred images. These limitations imposed by unimodal biometrics can be overcome by incorporating multimodal biometrics. Therefore, this paper presents a method that combines face and iris biometric traits with the weighted score level fusion technique to flexibly fuse the matching scores from these two modalities based on their weight availability. The dataset use for the experiment is self established dataset named Universiti Teknologi Malaysia Iris and Face Multimodal Datasets (UTMIFM), UBIRIS version 2.0 (UBIRIS v.2) and ORL face databases. The proposed framework achieve high accuracy, and had a high decidability index which significantly separate the distance between intra and inter distance. <s> BIB014
Biometric authentication is the science of establishing the identity of a user, towards a system, based on his/her physical or behavioral attributes BIB011 . During the last decade, the field of biometric authentication has gained growing popularity as biometric traits are becoming the next generation method that will widely replace the user name and password as the primary way of authentication, in the next 2-3 years. In addition to the idea that biometric characteristics are only useful in forensics, the pronounced necessity for reliable day-to-day transactions, has led to a range of applications that verify the identity of a person using human properties. Systems are increasingly being deployed and used throughout the world BIB012 , from limited simple home or business applications (the controlled access to a room), to large-scale projects, which are involved in societal functions, such as user verification for on-line transactions (e.g. banking ePayments, mobile devices). Finally, it is a common secret that biometrics have been used in the scope of surveillance themes. Remarkably, not only the industry, but also the military, law enforcement, and security agencies invest in the development and manufacture of facial, iris and voice recognition technologies, capable of detecting and identifying anyone. Traditional deployments are mainly uni-modal biometric systems and may have limited usage. The fact is that no single sample from the modality biometric is sufficiently accurate in real-world applications BIB006 , where it is demanded from designers to produce robust systems with low error rates and sufficient tamper proof protection  . Nevertheless, they constitute the starting point of each research into the direction of multibiometric systems which seeks to reduce some of their drawbacks  , by consolidating recognition process using multiple templates extracted from the same person (e.g., fingerprint, iris, face, hand geometry, gait, keystroke dynamics)  BIB001 . A biometric system is essentially a pattern recognition scheme that compares the tested features of a user with the stored ones, from the process of a previous enrollment. Each system can operate in identification or verification mode, where the system processes a measurement from which a biometrics template is extracted BIB007 . The concept of fusion in biometrics, helps to expand the feature space used to claim an identity, and thus, affects the matching accuracy of the system  . Multibiometric recognition in different levels of fusion can improve the performance, deter spoofing, and increase the overall accuracy of these systems. Considering these enrichments, the system will be more reliable and thus, more acceptable to be used in a number of related applications BIB002 BIB006 BIB008 . Studies in these areas BIB009 BIB013 BIB001 BIB003 BIB005 , aim to answer a crucial question: How can the leakage of stored biometric characteristics, to unauthorized individuals, be prevented? A variety of risks exist that call for protection of the stored elements, after the fusion of the templates. From a privacy viewpoint, most concerns against the common use of biometrics arise from the multiple modalities used to describe a single user, the sensitive nature of these data and the potential leakage of this information from devices that store it. Taking this into consideration, the security of the user's identity should be addressed, with a privacy perspective BIB010 and should be examined by different points of view. The elements that can reveal the identity of the user should be protected, while simultaneously, preventing him/her from opening multiple accounts using false data and covering the requirements for unique identifiers. Solutions such as the helper data system, fuzzy vault algorithms, cancelable biometrics and others come to promise improvements in this filed, while experimental studies have shown that these technologies can bring improved verification performance. Multibiometric template protection is the source that has motivated numerous works in the field of the combination of pattern recognition methodologies with the world of cryptography. From research perspective, results about the significant advantages in accuracy, reliability and security of biometric systems can promise protection of their storage. State-of-the-art proposals offer different scenarios to these concerns, while very recent experiments shift the target to the deployment of a unique generic category of systems BIB014  . The idea behind this statement is that the systems development will be able to support many applications based on multiple pieces of evidence under one human identity, capable of performing well on large-scale datasets. They should be designed in such a smart way that can offer overall security, beyond well-known risks or the nature of the transactions. This work is motivated by very recent advances in the areas of multibiometric recognition and biometric template protection, and its aim is to contribute to the studies of the interaction between biometrics and cryptography, presenting concrete, published results of the last four years. The time period of the works is carefully selected to serve the research in the entrance of biometrics in cryptography world, reflecting the increasing number of projects that aim to suggest solutions for the protection of user's identity, in case of risks during on-line transactions. These complementary security technologies can bring improvements in security and reliability of the systems, while strengthening public acceptance of the involved applications BIB004 . The remainder of this survey is organised as follows: In the next section, the importance of multimodalities against single modals is underlined, the different levels of fusion for multibiometric data are analysed, and template protection techniques are reviewed. Using this as the background of a new promising idea, the section of related work contains a comparative summary of multimodal biometrics and template protection in combination. The fourth section introduces the major privacy and security issues that arise. Finally, in the last section, a comprehensive conclusion, including the current approaches, is given and some remarks for discussion are presented.