Repeated Line Tracking and Multiline Neighbouring Relation (RLMN) framework for finger vein template security

In the era of rapid digitization, password management has become a significant challenge, prompting financial institutions to explore biometric alternatives for user authentication. Biometrics offers seamless and secure authentication, yet poses unique security risks, especially since biometric data cannot be changed if compromised. This keynote presents the Repeated Line Tracking and Multiline Neighbouring Relation (RLMN) framework, a novel approach for enhancing the security of finger vein templates in biometric systems. Emphasizing the importance of cancelability, this framework converts three-dimensional finger vein features into a single binary string, ensuring secure storage and robust authentication. We will explore its application in the banking sector, comparing it with other biometric systems, and discussing its potential to revolutionize identity verification. The session will also cover real-world implementations, such as those by Barclays and FinGo, and outline future research directions to address evolving security challenges in biometrics.