Paper Information

Towards Practical Biometric Key Generation with Randomized Biometric Templates

Lucas Ballard, Seny Kamara, Fabian Monrose, and Mike Reiter


Although biometrics have garnered significant interest as a source of entropy for cryptographic key generation, recent studies indicate that many biometric modalities may not actually offer enough uncertainty for this purpose. In this paper, we exploit a novel source of entropy that can be used with any biometric modality but that has yet to be utilized for key generation, namely associating uncertainty with the way in which the biometric input is measured. Our construction poses only a modest requirement on a user: the ability to remember a low-entropy password. We identify the technical challenges of this approach, and develop novel techniques to overcome these difficulties. Our analysis of this approach indicates that it may offer the potential to generate stronger keys: In our experiments, 40% of the users are able to generate keys that are at least 230 times stronger than passwords alone.