Biometric recognition technology has made significant advances over the last decade and is now used across a number of services and applications. However, this widespread deployment has also resulted in privacy concerns and evolving societal expectations about the appropriate use of the technology. For example, the ability to automatically extract age, gender, race, and health cues from biometric data has heightened concerns about privacy leakage. Face recognition technology, in particular, has been in the spotlight, and is now seen by many as posing a considerable risk to personal privacy. In response to these and similar concerns, researchers have intensified efforts towards developing techniques and computational models capable of ensuring privacy to individuals, while still facilitating the utility of face recognition technology in several application scenarios. These efforts have resulted in a multitude of privacy–enhancing techniques that aim at addressing privacy risks originating from biometric systems and providing technological solutions for legislative requirements set forth in privacy laws and regulations, such as GDPR. The goal of this overview paper is to provide a comprehensive introduction into privacy–related research in the area of biometrics and review existing work on Biometric Privacy–Enhancing Techniques (B–PETs) applied to face biometrics. To make this work useful for as wide of an audience as possible, several key topics are covered as well, including evaluation strategies used with B–PETs, existing datasets, relevant standards, and regulations and critical open issues that will have to be addressed in the future.

中文翻译：

---

增强隐私的面部生物识别技术：一项综合调查

生物识别技术在过去十年中取得了重大进展，现在已用于许多服务和应用程序。然而，这种广泛部署也导致了隐私问题和社会对适当使用该技术的期望。例如，从生物识别数据中自动提取年龄、性别、种族和健康线索的能力加剧了对隐私泄露的担忧。尤其是人脸识别技术一直备受关注，现在许多人认为它对个人隐私构成了相当大的风险。为了应对这些和类似的担忧，研究人员加紧努力开发能够确保个人隐私的技术和计算模型，同时仍然促进人脸识别技术在多个应用场景中的应用。这些努力催生了多种隐私增强技术，旨在解决源自生物识别系统的隐私风险，并为隐私法律法规（如 GDPR）中规定的立法要求提供技术解决方案。本概述文件的目标是全面介绍生物识别领域与隐私相关的研究，并回顾现有的工作应用于面部生物识别的生物识别隐私增强技术 (B-PET)。为了使这项工作对尽可能广泛的受众有用，还涵盖了几个关键主题，包括与 B-PET 一起使用的评估策略、现有数据集、相关标准和法规以及必须在未来。