A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> Since biometric data cannot be easily replaced or revoked, it is important that biometric templates used in biometric applications should be constructed and stored in a secure way, such that attackers would not be able to forge biometric data easily even when the templates are compromised. This is a challenging goal since biometric data are "noisy" by nature, and the matching algorithms are often complex, which make it difficult to apply traditional cryptographic techniques, especially when multiple modalities are considered. In this paper, we consider a "fusion " of a minutiae-based fingerprint authentication scheme and an SVD-based face authentication scheme, and show that by employing a recently proposed cryptographic primitive called "secure sketch ", and a known geometric transformation on minutiae, we can make it easier to combine different modalities, and at the same time make it computationally infeasible to forge an "original" combination of fingerprint and face image that passes the authentication. We evaluate the effectiveness of our scheme using real fingerprints and face images from publicly available sources. <s> BIB001 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <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> BIB002 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> Template protection techniques are used within biometric systems in order to protect the stored biometric template against privacy and security threats. A great portion of template protection techniques are based on extracting a key from or binding a key to a biometric sample. The achieved protection depends on the size of the key and its closeness to being random. In the literature it can be observed that there is a large variation on the reported key lengths at similar classification performance of the same template protection system, even when based on the same biometric modality and database. In this work we determine the analytical relationship between the system performance and the theoretical maximum key size given a biometric source modeled by parallel Gaussian channels. We consider the case where the source capacity is evenly distributed across all channels and the channels are independent. We also determine the effect of the parameters such as the source capacity, the number of enrolment and verification samples, and the operating point selection on the maximum key size. We show that a trade-off exists between the privacy protection of the biometric system and its convenience for its users. <s> BIB003 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> Public acceptance of biometric technology is hindered by security and privacy concerns regarding leakage of biometric templates. Biometric cryptosystems alleviate this problem by storing a secure sketch that is typically derived by binding the template with a cryptographic key. However, designing fingerprint cryptosystems is difficult because fingerprint matching is usually based on unordered sets of minutia features having large intra-user variations. To overcome this challenge, we propose a novel minutiae representation known as the Binarized Phase Spectrum (BiPS), which is a fixed-length binary string obtained by quantizing the Fourier phase spectrum of a minutia set. We secure the BiPS representation using a fuzzy commitment scheme employing turbo codes. We also propose a technique for aligning fingerprints based on the focal point of high curvature regions. The proposed system achieves a FNMR of 16.2% and 12.6% on FVC2002-DB1 and DB2 databases, respectively, at zero FMR. <s> BIB004 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> Random projection provides a good diversification effect for biometric template protection but is drawing increasing security concerns under the token-stolen (or public parameter) case. We propose a dynamic random projection method to alleviate these security concerns due to the stolen token by increasing the computational complexity to search for the unprotected biometric features. This is achieved by a projection process which dynamically assembles a random projection matrix from a set of candidate projection vectors. The selection of projection vectors is decided by the biometric feature vector itself and thus forms a nonlinear projection process. The proposed method permits the public and secure storage of all the candidate random vectors without the need for external secret keys. Experiments on the 800 samples in the database FVC2002DB2_A demonstrate the well-kept biometrie performance of the proposed method. <s> BIB005 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> The term biometrics refers to “automated recognition of individuals based on their behavioral and biological characteristics” (ISO/IEC JTC1 SC37). Several physiological (static) as well as behavioral (non-static) biometric characteristics have been exploited (Jain, Flynn & Ross, 2008) such as fingerprints, iris, face, hand, voice, gait, keystroke dynamics, etc., depending on distinct types of applications (see Figure 1). Biometric traits are acquired applying adequate sensors and distinctive feature extractors are utilized in order to generate a biometric template (reference data) in the enrollment process. During verification (authentication process) or identification (identification can be handled as a sequence of biometric comparisons against the enrollment records in a reference databse) the system processes another biometric measurement from which an according template is extracted and compared against the stored template(s) yielding acceptance/ rejection or hit/ no-hit, respectively. The presented work is motivated by very recent advances in the fields of multi-biometric recognition (Ross et al., 2006) and biometric template protection (Rathgeb & Uhl, 2011). Automatic recognition systems based on a single biometric indicator often have to contend with unacceptable error rates (Ross & Jain, 2003). Multi-biometric systems have improved the accuracy and reliability of biometric systems (Ross et al., 2006). Biometric vendors are already deploying multi-biometric systems (e.g. fingerprint and finger vein by SAFRAN Morpho1) and multi-biometric recognition is performed on large-scale datasets (e.g. within the Aadhaar project (Unique Identification Authority of India, 2012) by the Unique Identification Authority of India (UIDAI)). However, security of multi-biometric templates is especially crucial as they contain information regarding multiple traits of the same subject (Nagar et al., 2012). The leakage of any kind of template information to unauthorized individuals constitutes serious security and privacy risks, e.g. permanent tracking of subjects without consent (Ratha et al., 2001) or reconstruction of original biometric traits (e.g. fingerprints (Cappelli et al., 2007) or iris textures (Venugopalan & Savvides, 2011)) might become a realistic threat. Therefore, biometric template protection technologies have been developed in order to protect privacy and integrity of stored biometric data. However, so far, template protection schemes which provide provable security/ privacy, and achieve practical recognition rates have remained elusive, even on small datasets. This bookchapter provides a comprehensive overview of <s> BIB006 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> As biometric technologies are becoming pervasive, it is imperative to protect the users of these technologies from misuse of their biometric data. However, unlike user credentials in traditional security systems, such as passwords or tokens, biometric features cannot be consistently sampled, and the matching process can be complex. Furthermore, the consequences of losing biometric data can be far more severe than passwords or tokens. Secure sketches, a recently developed cryptographic primitive, allow noisy data to be restored using some helper-data, while providing bounds on how much sensitive information such helper-data would reveal when obtained by malicious parties. In this chapter, we discuss security threats on the use of biometric templates in security systems, and how secure sketches can be used to address these threats under various circumstances. <s> BIB007 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Multibiometric Template Protection <s> Abstract In this work adaptive Bloom filter-based transforms are applied in order to mix binary iris biometric templates at feature level, where iris-codes are obtained from both eyes of a single subject. The irreversible mixing transform, which generates alignment-free templates, obscures information present in different iris-codes. In addition, the transform is parameterized in order to achieve unlinkability, implementing cancelable multi-biometrics. Experiments which are carried out on the IITD Iris Database version 1.0 confirm the soundness of the proposed approach, (1) maintaining biometric performance at equal error rates below 0.5% for different feature extraction methods and fusion scenarios and (2) achieving a compression of mixed templates down to 10% of original size. <s> BIB008
Current literature in biometric template protection, key approaches to cryptosystems or cancelable biometrics and multiple biometric templates from the same source have been examined. Early studies, which required an alignment of biometric templates, have demonstrated efficiency with specific combinations of personal data. Different techniques have been proposed to overcome the shortcomings of pre-alignment methods BIB006 BIB002 . Some of the schemes have been applied to physiological or behavioral biometrics BIB001 . Respecting the necessity for use the most easily captured biometric features, from a pattern recognition aspect, biometrics have been selected to map biohashing, block permutation, fuzzy vaults and commitments schemes BIB003  . As a second approach, the collaboration of template protection with multibiometrics can be achieved with several notable approaches that have been proposed and evaluated according to the ability to correct the error ratio. For example, multi-algorithm fusion at feature level, multibiometric cryptosystem fuzzy vault based on fingerprint and iris BIB004 , fuzzy commitments for face BIB005 and other ideas for score fusion level were successfully applied to fingerprints with security advances and many other combinations under various scenarios have been proposed during the last three years BIB008 BIB004 . The target is to provide a uniform distribution of errors  , combining successfully the data and covering research gaps of previous works, and thus, contributing to secure, stable systems BIB007  , while offering, a fast comparison of protected templates suitable for biometric recognition in identification mode.