An Improved Biometric Template Protection Method based on Non-Uniform Quantization

In recent literature, the issue of biometric template protection was raised. Some schemes were proposed to solve the contradiction between the fuzzy biometric information and accurate cryptography functions to achieve the protection of biometric template via cryptography method. In this paper, a novel methodology to achieve the security of the biometric templates in biometric systems is proposed. An adaptive non-uniform quantization (ANUQ) algorithm is introduced to eliminate the contradiction between the fuzziness of the biometric information and the sensitive of the Hash function. The ANUQ algorithm maps different biometric feature vectors from the same individual to a unique quantized feature vector. Then the quantized feature vector can be saved and identified by its hash and the biometric system can be free from the risk of the leakage of users’ privacy information. Based on the ANUQ algorithm, two biometric template protection scheme are designed to meet different applications. Scheme-I involved a single quantizing template while scheme-II use a quantizing template array. The comparison of the two schemes are raised. Further, the testing of these schemes are carried out on an iris recognition algorithm. The results show the feasibility of the ANUQ-based schemes.