Evaluation of privacy and security implications of biometric authentication systems: challenges and solutions.

该项目属于EPSRC普适和普适计算研究领域。用户身份验证通常依赖于基于密码的机制。随着用户拥有的账号数量的增加，密码成为了一个恼人的负担，因为用户需要记住几十个密码。近年来，用户设备(如手机、平板电脑、智能手表)变得越来越强大，价格越来越便宜，传感器越来越丰富，这使得生物特征识别成为一种可行的身份验证工具。尽管人们对生物特征识别的性能指标--错误接受率和错误拒绝率--给予了很大的关注，但很少有人关注更强大的威胁模型。为了实现对认证系统安全和隐私保障的真实评估，必须考虑具有更多能力和/或知识的攻击者。在本项目中，我们将评估新型威胁模型对生物特征认证系统的影响。将被分析的主要因素之一是生物特征信息的可收集性。随着用户设备附带的传感器的普及，生物识别技术现在已经很普遍了。这意味着，对手可以通过几个过去不存在的渠道获得生物识别。经典的例子是指纹，可以从饮水杯或受害者触摸的其他表面收集，或者面部照片，可以很容易地找到并从社交媒体下载。更新的场景可能涉及物联网设备监听用户的语音，或者恶意软件感染配备了指纹的智能手机来窃取用户的指纹。此外，认证系统设计者必须考虑生物特征信息的不可撤销性。与密码相反，密码可以重置，一旦生物特征被披露，其保密性就会永久丧失。该项目旨在分析生物识别系统在引入未探索的威胁模型方面的挑战，并调查可能的对策。这些方面的评估将使人们更深入地了解部署基于生物特征的认证系统的影响。该项目包含在普适和普适计算的研究领域，并在普适和普适系统中与网络安全相关的挑战中得到了很好的描述。我们将作为行业合作伙伴与万事达卡合作，以便在现实世界的使用案例(例如移动支付、在线身份)中验证我们的研究。

This project falls within the EPSRC Pervasive and ubiquitous computing research area. User authentication commonly relies on password-based mechanisms. With the increase in the number of accounts owned by users, passwords became an annoying burden, as users are required to memorize dozens of them.In recent years, user devices (e.g., mobile phones, tablets, smartwatches) are becoming more powerful, affordable, and rich of sensors, which made biometric recognition one viable instrument for authentication.While a lot of attention has been placed on the performance metrics of the biometric recognition, that is the false accept rate and thefalse reject rate, little emphasis has been placed to more powerful threat models. Adversaries with increased capabilities and/or knowledge must be considered in order to achieve a realistic evaluation of the authentication system security and privacy guarantees.In this project, we will evaluate the impact of novel threat models on biometric authentication systems. One of the main factor that will be analyzed is the collectability of biometric information. With the pervasiveness of sensors that come with user devices biometrics are now widespread. This means that biometrics can be obtained by an adversary through several channels that did not exists in the past. Classic examples are fingerprints, that can be collected from drinking glasses or other surfaces that the victim has touched, or face pictures, that can be easily found and downloaded from social medias. Newer scenarios might involve IoT devices listening to the user's voice, or malware infecting fingerprint-equipped smartphones to steal the user's fingerprints. Furthermore, authentication system designers must consider the irrevocability of biometric information. Contrary from passwords, that can be reset, once a biometric trait has been disclosed, its confidentiality is lost in a permanent way. This project aims to analyze challenges of biometric systems, regarding the introduction of unexplored threat models, and to investigate possible countermeasures. The evaluation of such aspects will enable a deeper understanding of the implications of deploying biometric-based authentication systems.This project is comprised in the research area of pervasive and ubiquitous computing, and is well-described in the challenges related to cyber-security in pervasive and ubiquitous systems. We will collaborate with Mastercard as an industrial partner in order to validate our research in real-world use cases (e.g., mobile payments, online identity).