Abstract
The biometric-based keys generation represents the utilization of the extracted features from the human anatomical (physiological) traits like a fingerprint, retina, etc. or behavioral traits like a signature. The retina biometric has inherent robustness, therefore, it is capable of generating random keys with a higher security level compared to the other biometric traits. In this paper, an effective system to generate secure, robust and unique random keys based on retina features has been proposed for cryptographic applications. The retina features are extracted by using the algorithm of glowworm swarm optimization (GSO) that provides promising results through the experiments using the standard retina databases. Additionally, in order to provide high-quality random, unpredictable, and non-regenerated keys, the chaotic map has been used in the proposed system. In the experiments, the NIST statistical analysis which includes ten statistical tests has been employed to check the randomness of the generated binary bits key. The obtained random cryptographic keys are successful in the tests of NIST, in addition to a considerable degree of aperiodicity.
Keywords
Chaotic map, Glowworm Swarm Optimization (GSO), Randomcryptographic key generation, Retina
Article Type
Article
How to Cite this Article
Mazher, Alaa Noori and Waleed, Jumana
(2022)
"Retina Based Glowworm Swarm Optimization for Random Cryptographic Key Generation,"
Baghdad Science Journal: Vol. 19:
Iss.
1, Article 17.
DOI: https://doi.org/10.21123/bsj.2022.19.1.0179