TWC: Small: Protecting Privacy of Biometric Data throughout Computation

计算机视觉的进步使生物认证和识别变得比以前更可靠和更容易获得，这使得这种数据的无处不在的使用远远超过传统认证的潜力。显然，需要保护高度敏感的生物识别技术，与用于身份验证目的的其他类型的数据不同，这些数据不能被撤销并被新的值取代。这意味着，与丢失其他敏感数据相比，任何对生物特征数据安全的破坏都会对个人造成深远的后果。以前，只有有限的机制可用于保护生物特征数据的隐私。为了解决缺乏足够的保护机制的问题，该项目开发了新的技术，用于在不完全信任或不完全安全的环境中处理和使用生物特征数据时增强其隐私保护，这些环境和应用程序远远超出了比较两个生物特征代码的范围。该项目的范围包括(I)生物特征数据的安全交互计算，(Ii)安全地将生物特征计算外包给不可信的服务器，以及(Iii)有效地验证外包计算结果的正确性。这项工作的一个明显好处是，它将密码设计与对真实生物特征数据的实际评估相结合，并包括将开发的工具集成到生物特征计算网格环境中。这项研究的结果预计将支持和促进在处理敏感生物识别数据方面的更安全做法，包括利用不可信的计算能力，以及在其他情况下不被允许共享其数据的实体之间更广泛的合作。

Progress in computer vision makes biometric authentication and recognition become more reliable and readily available than before, with a potential for ubiquitous use of such data well beyond traditional authentication. The need to protect highly sensitive biometrics is apparent, which, unlike other types of data used for authentication purposes, cannot be revoked and replaced with a new value. This means that any breach in security of biometric data has far reaching consequences to the individual than loss of other sensitive data.Previously, only limited mechanisms for protecting privacy of biometry were available. To address the paucity of adequate protection mechanisms, this project develops novel techniques for enhancing privacy protection of biometric data when it is being processed and used in environments which are not fully trusted or secured in a broad set of contexts and applications that go well beyond comparing two biometric codes. The project's scope covers (i) secure interactive computation on biometric data, (ii) secure outsourcing of biometric computation to untrusted servers, and (iii) efficient verification of the correctness of the result of outsourced computation. A distinct benefit of this work is that it combines cryptographic design with practical evaluation on real biometric data, as well as includes integration of developed tools into a biometric computing grid environment. The outcomes of this research are expected to enable and promote safer practices in handing sensitive biometric data, including utilizing untrusted computing power, and a wider degree of collaboration between entities who are otherwise not permitted to share their data.