A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Decision Level Fusion. <s> With the pace of increasing online transactions and communication, the demand for security and privacy increases. To protect confidential information and to authenticate people electronically, several solutions already introduced. Traditional biometric systems that are based on single biometric usually suffer from problems like impostorspsila attack or hacking, unacceptable error rates. To improve security and privacy and systempsilas reliability two or more biometrics of the same identity could be combined in a method that enhances the efficiency of the system. The biometric information, however, is irreplaceable information, when it is compromised. Thereby, one must give a special attention to protection of such information. We propose a novel protection technique for the biometric information, especially the feature information and the templates. The point of our proposal is securely embeds and extracts an iris template in a fingerprint image using a combined DWT and LSB based biometric watermarking algorithm in each authentication. The embedded data travel through insecure communication line like the Internet, and they are used in matching process. This technique causes security against eavesdropping and replay attacks on the Internet, because the watermark embedded transmitted data are used in the authentication session after watermark extraction. <s> BIB001 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Decision Level Fusion. <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> BIB002 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Decision Level Fusion. <s> In this paper, we propose a new finger multi-biometric cryptosystem using feature-level fusion to simultaneously protect multiple templates of fingerprint, finger vein, finger knuckle print and finger shape traits as a single secure sketch. We theoretically analyze the featurelevel fusion for finger multi-biometric cryptosystem with respect to their impact on security and recognition accuracy. The comparative experimental results ascertain that finger multibiometric cryptosystem outperforms the uni-biometric counterparts in terms of verification performance and template security. <s> BIB003 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Decision Level Fusion. <s> On 14th October 2013 the European Parliament Committee on Industry, Research and Energy (ITRE) paved the way on the regulation and harmonisation for electronic identification, authentication and trust services (eIDAS) between EU member states. This upcoming regulation will ensure mutual recognition and acceptance of electronic identification across borders, which also provides an opportunity to establish trusted electronic transactions in the Single Euro Payments Area (SEPA). The contribution of the presented paper is twofold: on the one hand we discuss the adaption of the upcoming eIDAS standard towards trusted banking transactions and outline resulting security and privacy enhancements; on the other hand we extend the eIDAS standard by biometric authenticated transactions which not only boost user convenience, trust and confidence towards eBanking and eBusiness, but suggest to integrate state-of-the-art privacy compliant biometric technologies into the security ecosystem, which is promoted by both, the European Payment Council (EPC) and the European Banking Union (EBU). As a result we identify eIDAS as highly suitable for banking transactions since it is solely based on security protocols and infrastructure which have been for more than ten years proven secure in the civil aviation domain. <s> BIB004 </s> A Survey on Multimodal Biometrics and the Protection of Their Templates <s> Decision Level Fusion. <s> Recently, forensic science has had many challenges in many different types of crimes and crime scenes, vary from physical crimes to cyber or computer crimes. Accurate and efficient human identification or recognition have become crucial for forensic applications due to the large diversity of crime scenes, and because of the increasing need to accurately identify criminals from the available crime evidences. Biometrics is an emerging technology that provides accurate and highly secure personal identification and verification systems for civilian and forensic applications. The positive impact of biometric modalities on forensic science began with the rapid developments in computer science, computational intelligence, and computing approaches. These advancements have been reflected in the biometric modality capturing process, feature extraction, feature robustness, and features matching. A complete and automatic biometric identification or recognition systems have been built accordingly. This chapter presents a study of the impacts of using some biometric modalities in forensic applications. Although biometrics identification replaces human work with computerized and automatic systems in order to achieve better performance, new challenges have arisen. These challenges lie in biometric system reliability and accuracy, system response time, data mining and classification, and protecting user privacy. This chapter sheds light on the positive and the negative impacts of using some biometric modalities in forensic science. In particular, the impacts of fingerprint image, facial image, and iris patterns are considered. The selected modalities are covered preliminarily before tackling their impact on forensic applications. Furthermore, an extensive look at the future of biometric modalities deployment in forensic applications is covered as the last part of the chapter. <s> BIB005
This level fusion is termed so because it depends on the final, acceptance or rejection, decisions. Auxiliary information is available to systems with high dependence from the application. Gathering the information by independent sub-systems, and fusing the results, constitutes a way to increase the overall precision, supporting the idea for universality of the entire system BIB003 . Mainly, the conducted research in this area is still immature. Fusion schemes that incorporate parts into a whole final scheme have not been yet explored BIB002 . Suggestions for combining soft biometric characteristics BIB001 , like the gender, age or the ethnicity of the user, with the inputs of biometric samples, can be used to verify the person's identity. The presented themes provide an overview of the first tendency to the direction of covering the problematic areas of conventional biometric systems. The combination of popular traits, such as the iris and the fingerprints, is embedded in many applications. The conducted tests demonstrate advantages, while introducing new tasks. The evaluation of a complete biometric system is a complex issue and requires stronger user involvement for feature level schemes BIB004 . Compact multibiometric templates need to be generated, offering, in this way, an improved concrete content of information. Nevertheless, the most important drawback of fusion is the central storage of the data, coming from the same or different sources. This is a complex characteristic that should be addressed in order to prevent further privacy threats. Last, but not least, the precision of the model feature distributions, and the estimation of the possibilities to practice the theory in large databases, are still intricate issues BIB005 .