Biometric template protection based on Bloom filters and honey templates

Biometric verification can be considered one of the most reliable approaches to person authentication. However, biometrics are highly sensitive personal data and any information leakage poses severe security and privacy risks. Biometric templates should hence be protected and impersonation with stolen templates must be prevented, while preserving system's performance. In this study, a general biometric template protection scheme based on honey templates and Bloom filters is proposed, in order to grant privacy protection to the enrolled subject and detect the use of stolen templates. The performance and security evaluations show the soundness of the proposed scheme for facial verification. The benchmark is conducted with the publicly available BioSecure Multimodal DB and the free Bob image processing toolbox, so that research is fully reproducible.