Teo-Beng Jin
Yonsei University
About the Lab
Professor Teo-Beng Jin's research lab specializes in biometric security and privacy-preserving technologies, with a primary focus on developing robust and efficient biometric template protection methods. The lab explores advanced techniques in biometric discretization, revocable template generation, and secure feature encoding to ensure strong privacy and security in biometric systems. Key research directions include enhancing system performance while maintaining non-invertibility, diversity, and revocability in fingerprint-based authentication. The lab also investigates novel encoding schemes and feature selection methods to improve the reliability and security of biometric systems in real-world applications.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
2With the wide deployment of biometric authentication systems, several issues pertaining security and privacy of the biometric template have gained great attention from the research community. To resolve these issues, a number of biometric template protection methods have been proposed. However, the design of a template protection method to satisfy four criteria, namely diversity, revocability and non-invertibility is still a challenging task, especially performance degradation when template prot
Biometric discretization is a process of transforming continuous biometric features of an identity into a binary bit string. This paper mainly focuses on improving the global discretization method – a discretization method that does not base on information specific to each user in bitstring extraction, which appears to be important in applications that prioritize strong security provision and strong privacy protection. In particular, we demonstrate how the actual performance of a global discreti
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