Abstract
Fuzzy Commitment Scheme is a popular technique for biometric template protection. The idea is to bind an random bit string with a biometric template in binary format called difference vector. Ideally, a difference vector is infeasible to recover either the biometric template or the random bit string without any knowledge of the user's biometric data. Yet, this is only valid if the biometric template is uniformly random, which is not the case in reality. In this paper, we propose a method known as Randomized Dynamic Quantization transformation to binarize biometric data. The transformed bit strings are highly distinctive among the users and near to uniformly random. We demonstrate the implementation in the context of fingerprint biometrics.
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