On July 8th Daile Osorio-Roig defended her PhD thesis on Privacy-Preserving Workload Reduction in Biometric Systems. Congratulations!
From the abstract:
The development of large-scale biometric identification systems that provide privacy protection of the enrolled subjects is an ongoing concern. Most importantly, biometric technologies demand interoperability and deployment assuring maximum usability by including multi-modal biometric solutions. In the context of privacy protection, several Biometric Template Protection (BTP) schemes have been proposed in the past. However, these schemes appear to be unsuitable for indexing (Workload Reduction (WR)) in biometric identification systems. As a consequence, they have been utilised in biometric identification systems performing exhaustive searches (i. e. one-to-many search), which represent a time-consuming task and, hence, a high computational workload dominated by the number of comparisons. Additionally, novel privacy protection schemes have recently been developed in the literature. These approaches appear promising but have not yet been evaluated in a detailed way, especially in terms of their privacy protection capabilities. Motivated by the acceleration of large-scale protected biometric database searches and the investigation for privacy enhancement, this thesis investigates in more detail indexing schemes operating on protected templates for different biometric characteristics, as well as some limitations in privacy protection. Extensive experimental evaluations demonstrate that novel BTP-agnostic and biometric characteristic (BC)-agnostic indexing schemes can successfully reduce the computational workload of a biometric system while preserving biometric security and performance. Novel attacks have also been proposed in the context of privacy protection.