Biometric Authentication Methods on Mobile Platforms: An Introduction to Fingerprint Strong Feature Extraction - DJARA, Tahirou; Edoh, Agnitè Maxim Wilfrid Straiker (My University, 2023)
In this work, the authors propose a new biometric authentication system on mobile devices, enhancing security at these terminals and preserving user privacy. The proposed system uses a method of extracting strong features from minutiae with refinement of the method with regard to the further elimination of false minutiae by the calculation of geometric information (orientations and distances between minutiae) to obtain true terminations and stronger bifurcations facilitating the recognition of individuals. A series of tests carried out using a recognition and authentication application allowed us to achieve a false rejection rate of 13.81% and a false acceptance rate of almost zero (0.021%). The authors also propose a security model using hash functions and a random number to make the recognition system revocable, more difficult to compromise and thus reducing the risk of usurpation.
Keywords: Biometric Authentication; Fingerprint; Minutiae Extraction; Mobile Devices; Recognition; Strong Features