A New Biometric Template Protection using Random Orthonormal Projection and Fuzzy Commitment
This work addresses biometric template protection for authentication systems, but it appears incremental as it builds on existing approaches.
The authors tackled the problem of securing biometric templates in authentication systems by proposing a hybrid approach combining feature transformation and biometric cryptosystem methods, achieving maintained system performance with reduced computational complexity and guaranteed security.
Biometric template protection is one of most essential parts in putting a biometric-based authentication system into practice. There have been many researches proposing different solutions to secure biometric templates of users. They can be categorized into two approaches: feature transformation and biometric cryptosystem. However, no one single template protection approach can satisfy all the requirements of a secure biometric-based authentication system. In this work, we will propose a novel hybrid biometric template protection which takes benefits of both approaches while preventing their limitations. The experiments demonstrate that the performance of the system can be maintained with the support of a new random orthonormal project technique, which reduces the computational complexity while preserving the accuracy. Meanwhile, the security of biometric templates is guaranteed by employing fuzzy commitment protocol.