TWC: Small: Imparting Privacy to Biometric Data in Cyberspace

TWC：小型：为网络空间中的生物识别数据提供隐私

• 批准号: 1618518
• 负责人: Arun Ross
• 金额: $ 49.88万
• 依托单位: Michigan State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-10-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1618518&HistoricalAwards=false
• 关键词: TWC; Small; Imparting; Privacy; Biometric

Recent work has established the possibility of deriving auxiliary information from biometric data. For example, it has been shown that face images can be used to deduce the health, gender, age and race of a subject; further, face images have been used to link a pseudonymous profile in the Web with a true profile, thereby compromising the privacy of an individual. The objective of this work is to design and implement techniques for imparting privacy to biometric data such as face, fingerprint and iris images. In this regard, the following tasks are being conducted: (a) methods to modify biometric data such that the modified data can be used for re-identifying an individual but cannot be used to derive auxiliary information about the subject, such as gender and age; (b) methods to generate multiple privacy-enhanced templates from the same biometric data in such a way that these templates cannot be linked using a biometric matcher; and (c) methods to decompose and store the biometric data of a subject across entities such that individual entities cannot determine the identity of the subject, but collaboration across entities is essential for eliciting the identity of the subject. Finally, methods to assess the degree of privacy of a biometric image are being developed in order to quantify the amount of private information that can be derived from it. The proposed methods are being evaluated on publicly available face, fingerprint and iris datasets in order to determine their efficacy in the context of cyberspace applications.

最近的工作已经确立了从生物测定数据中获得辅助信息的可能性。例如，已经证明面部图像可用于推断受试者的健康、性别、年龄和种族；此外，面部图像已被用于将网络中的假名简档与真实简档相关联，从而危及个人隐私。这项工作的目标是设计和实现赋予生物特征数据(如面部、指纹和虹膜图像)隐私的技术。在这方面，正在执行以下任务：(A)修改生物测定数据的方法，使得修改后的数据可用于重新识别个体，但不能用于导出关于对象的辅助信息，例如性别和年龄；(B)从相同的生物测定数据生成多个隐私增强模板的方法，其方式是这些模板不能使用生物测定匹配器链接；以及(C)跨实体分解和存储对象的生物测定数据的方法，使得各个实体不能确定对象的身份，但是跨实体的协作对于得出对象的身份是必不可少的。最后，正在开发评估生物特征图像的隐私程度的方法，以便量化从该图像中可以获得的私人信息量。目前正在对公开可用的人脸、指纹和虹膜数据集评估拟议的方法，以确定其在网络空间应用方面的有效性。