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Biometrics is a universally used automatic identification of persons, depending on their behavioural and biological quality. Biometric authentication plays a crucial role in the identity management system. Safety of biometric authentication systems needs to be addressed as there are still some points related to the integrity and public receiving of biometric systems. Feature extraction module of biometric authentication systems, during the season of enrolment scanned biometric information to extract the set of salient features. This set of unique feature is known as biometric template. This biometric template is helpful in distinguishing between different users. These templates are generally stored during the time of enrolment in a database indexed by the user's identity information. The biometric template protection is an important issue because the compromised template cannot be cancelled and reissued like a password or token. Template protection is a challenging task because of intra user variability present in the acquired biometric traits. This paper surveys about different existing approaches for designing a protection scheme for biometric templates with their strength and boundaries existing in the literature. Some prospect information in designing template protection schemes are also addressed in this paper.
A Post-Quantum Biometric Template Protection Scheme Based on Learning Parity With Noise (LPN) Commitments
