You are presented with multiple paper abstracts, alongside the associated literature review and chapter titles. Given the provided information, you are going to do a literature review. Please generate a coherent literature review that synthesizes the content, draws connections between different works, highlights major findings, and identifies any gaps in the existing research.

Literature Review Title: A Survey on Multimodal Biometrics and the Protection of Their Templates 
Chapter Title:  Multibiometric System Recognition 
1. Abstract of Cited Paper (BIB001):  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. 
2. Abstract of Cited Paper (BIB002):  In credential systems, which allow the construction of privacy-preserving access control infrastructures in online environments, credential transfer occurs when Alice gives her private key to another entity who can then freely use Alice's credential as if it was his/her own. Prior approaches to limit credential transfer require tamper-resistant user hardware, or are ineffective against closely knit groups of users who are willing to share personal or valuable information with each other. In this paper we propose a scheme to achieve non-transferability for any malicious, but computationally bounded, legitimate credential owner. Copyright © 2009 John Wiley & Sons, Ltd. 
3. Abstract of Cited Paper (BIB003):  This chapter discusses the performance of five different iris segmentation algorithms on challenging periocular images. The goal is to convey some of the difficulties in localizing the iris structure in images of the eye characterized by variations in illumination, eyelid and eyelash occlusion, de-focus blur, motion blur, and low resolution. The five algorithms considered in this regard are based on the (a) integro-differential operator; (b) hough transform; (c) geodesic active contours; (d) active contours without edges ; and (e) directional ray detection method. Experiments on the Face and Ocular Challenge Series (FOCS) Database highlight the pros and cons of the individual segmentation algorithms.

Literature Review:
Data fusion in biometric systems is commonly an active area with numerous applications being not only a solution to the problems of uni-modalities, but also an active research field BIB003 BIB002 . Vendors are already deploying systems that use two or three patterns for the same user, providing recognition even on largescale datasets. Information fusion constitutes a way to enhance the matching accuracy of the system without resorting to other measurements or techniques, but just, being based only on the template. Information Fusion. The three different factors of recognition performance of the gathered data are given in the following list. Feature Level Fusion. The specific method comprises the strategies which pertain to the sensor, the set, rank and decision level. For the first one, in a concrete way, it is worth to be mentioned that this fusion level involves augmenting the vectors arising from the extractors and subjecting the vector to a transformation algorithm BIB004 BIB001 . The elements can enhance the performance. Furthermore, information from multiple feature sets can be used to refine the template. Using the third category, a rank level fusion is suitable for biometric systems operating in the identification mode. Finally, the last level fusion consists of artifacts coming from the final outputs of an individual sub-system, and wisely is mentioned as the simplest form of fusion. The correlation between the main inputs has to be examined, in order to evaluate the improvements in matching performance.