CRII: SaTC: Searchable Encryption for Biometric Data

CRII：SaTC：生物特征数据的可搜索加密

• 批准号: 1849904
• 负责人: Benjamin Fuller
• 金额: $ 17.47万
• 依托单位: University of Connecticut
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-02-15 至 2021-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1849904&HistoricalAwards=false
• 关键词: CRII; SaTC; Searchable; Encryption; Biometric

Biometrics are part of modern citizens' identity. Individuals' mobile devices collect facial, iris, fingerprint, and electrocardiogram data. Border checkpoints collect travelers' biometrics. National identity cards use biometrics to identify individuals. In many applications, a large group of users' biometrics are stored together in a centralized database. This type of widespread and expanding use of biometrics creates privacy concerns as biometrics are correlated to sensitive attributes such as race, gender, and disease risk factors. Protecting this data balances needs and citizens' privacy. This project designs a new system that allows identification while retaining privacy of non-relevant individuals when querying centralized biometric databases. The system design uses cryptography to provide rigorous security claims.Searchable encryption allows a database to process queries without knowing the underlying data. Current biometrics are characterized by noise between repeated readings. This project designs two systems which both build on searchable encryption and noise tolerant cryptography. The first system combines selective locality sensitive hashes and searchable encryption to retrieve records that match many locality sensitive hash outputs. The second system builds a variant of inner-product encryption that retrieves only the set of close records. The superior of the two designs will be implemented and benchmarked. An important aspect of any searchable encryption design is its leakage profile. As such, the implemented scheme's leakage is evaluated with respect to the known statistical properties of an identified biometric.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

生物识别技术是现代公民身份的一部分。个人的移动的设备收集面部、虹膜、指纹和心电图数据。边境检查站收集旅客的生物识别信息。 国家身份证使用生物识别技术来识别个人。在许多应用中，大量用户的生物特征被一起存储在集中式数据库中。 生物识别技术的这种广泛和不断扩大的使用产生了隐私问题，因为生物识别技术与种族，性别和疾病风险因素等敏感属性相关。保护这些数据平衡了需求和公民隐私。 该项目设计了一个新的系统，允许识别，同时保留隐私的非相关个人查询时，集中的生物特征数据库。 系统设计使用密码学来提供严格的安全声明。可搜索加密允许数据库在不知道底层数据的情况下处理查询。 当前的生物识别特征在于重复读数之间的噪声。这个项目设计了两个系统，这两个系统都建立在可搜索加密和噪声容忍加密。 第一个系统结合了选择性局部敏感散列和可搜索加密，以检索与许多局部敏感散列输出匹配的记录。 第二个系统构建了一个内积加密的变体，它只检索关闭记录集。 将实施两种设计中的上级设计并进行基准测试。 任何可搜索加密设计的一个重要方面是其泄漏配置文件。 该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Resist: Reconstruction of irises from templates

• DOI: 10.1109/ijcb48548.2020.9304912
• 发表时间: 2020-07
• 期刊: 2020 IEEE International Joint Conference on Biometrics (IJCB)
• 作者: Sohaib Ahmad;Benjamin Fuller

Cryptographic Authentication from the Iris

• DOI: 10.1007/978-3-030-30215-3_23
• 发表时间: 2019-09
• 作者: Sailesh Simhadri;James Steel;Benjamin Fuller

Computational fuzzy extractors

计算模糊提取器

• DOI: 10.1016/j.ic.2020.104602
• 发表时间: 2020
• 期刊: Information and Computation
• 影响因子: 1
• 作者: Fuller, Benjamin;Meng, Xianrui;Reyzin, Leonid
• 通讯作者: Reyzin, Leonid

Continuous-Source Fuzzy Extractors: Source uncertainty and insecurity

• DOI: 10.1109/isit.2019.8849421
• 发表时间: 2019-07
• 期刊: 2019 IEEE International Symposium on Information Theory (ISIT)
• 作者: Benjamin Fuller;Lowen Peng

ThirdEye: Triplet Based Iris Recognition without Normalization

• DOI: 10.1109/btas46853.2019.9185998
• 发表时间: 2019-07
• 期刊: 2019 IEEE 10th International Conference on Biometrics Theory, Applications and Systems (BTAS)
• 作者: Sohaib Ahmad;Benjamin Fuller