Abstract

Fingerprints remain consistent and stable throughout a human’s lifetime. This research exhibits the utilization of fingerprint bio-metrics to generate secured keys for improved security. The main contribution is the generation of 87 keys, achieved by enhancing the fingerprint image and sharpening it with a Laplacian filter. Three types of geometrical shapes, such as circle, square, and triangle, are separately drawn on the fingerprint after binarization, morphological operations, and thinning. Each shape is drawn five times on the fingerprint with different radii for each type. The end and bifurcation points, are extracted as features inside and outside these shapes. Chaotic-Pseudo-Random-Number Generator (CPRNG) technique is used and the generated keys are merged with those generated from minutiae (end and bifurcation) points' positions. The process was implemented using MATLAB R2021b. The simulation results demonstrate that it is difficult to crack the keys generated by this technique because the attacker requires a very high time, almost 7.5595e+159 years to decrypt the encrypted message. This time is greater than the time required to crack the keys generated in some previous research as compared to them. Therefore, the proposed technique enhances the privacy and security. The results confirm the possibility of this technique opening opportunities for future developments and innovations. The technique can be used via deep learning in fingerprint identification, recognition, and key generation mechanisms.