In a biometric recognition system, the matcher compares an old and a fresh template to decide if it is a match or not. Beyond the binary output (`yes' or `no'), more information is computed. This paper provides an in-depth analysis of information leakage during distance evaluation, with an emphasis on threshold-based obfuscated distance (\textit{i.e.}, Fuzzy Matcher). Leakage can occur due to a malware infection or the use of a weakly privacy-preserving matcher, exemplified by side channel attacks or partially obfuscated designs. We provide an exhaustive catalog of information leakage scenarios as well as their impacts on the security concerning data privacy. Each of the scenarios leads to generic attacks whose impacts are expressed in terms of computational costs, hence allowing the establishment of upper bounds on the security level.

翻译：在生物特征识别系统中，匹配器通过比对旧模板与新模板来判断是否匹配。除二元输出（"是"或"否"）外，系统还会计算更多信息。本文深入分析了距离评估过程中的信息泄露问题，重点关注基于阈值的模糊距离（即模糊匹配器）。信息泄露可能源于恶意软件感染或弱隐私保护型匹配器的使用，典型场景包括侧信道攻击或部分模糊化设计。我们系统梳理了各类信息泄露场景及其对数据隐私安全的影响，每个场景均会导致通用攻击，其影响以计算复杂度形式量化，从而可建立安全等级的上界约束。