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:  Score Level Fusion. 
1. Abstract of Cited Paper (BIB001):  Data security and privacy are crucial issues to be addressed for assuring a successful deployment of biometrics-based recognition systems in real life applications. In this paper, a template protection scheme exploiting the properties of universal background models, eigen-user spaces, and the fuzzy commitment cryptographic protocol is presented. A detailed discussion on the security and information leakage of the proposed template protection system is given. The effectiveness of the proposed approach is investigated with application to online signature recognition. The given experimental results, evaluated on the public MCYT signature database, show that the proposed system can guarantee competitive recognition accuracy while providing protection to the employed biometric data. 
2. Abstract of Cited Paper (BIB002):  Traditional criteria used in biometric performance evaluation do not cover all the performance aspects of biometric template protection (BTP) and the lack of well-defined metrics inhibits the proper evaluation of such methods. Previous work in the literature focuses, in general, on a limited set of criteria and methods. This paper provides the first holistic approach to the evaluation of biometric template protection that is able to cover a whole range of methods. We present a selection of well-defined criteria and some metrics that are compliant with the reference architecture for template protection as defined in the recently adopted standard ISO/IEC 24745 (2011), which is applicable to nearly all known BTP methods. The criteria have been grouped in three categories of performance: technical, protection, and operational.

Literature Review:
On this level of fusion, matching scores are returned by each individual sub-system and the obtained output scores are combined. The suggested ways underline the necessity for a normalised score, aiming to improve the reliability of the system. There are three basic groups: density based, transformation based and classifier based schemes. The performance of each scheme depends on the quantity and the quality of the involved informative data. Major issues, like the limited number of the available training samples, or, the lack of homogeneity, can be further investigated, using the previously mentioned approaches BIB002 . To conclude, always considering that a multibiometric system is affected by the correlation BIB003 , the combination of the weak uncorrelated biometric matchers can lead to better performance, than combining the strong ones, positively correlated. Using this starting point, score level becomes the most popular level among the others, and uncorrelated traits are applied in recognition systems, increasing, successfully, the desirable accuracy BIB001 .