期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2021
卷号：12
期号：7
DOI：10.14569/IJACSA.2021.0120772
语种：English
出版社：Science and Information Society (SAI)
摘要：Chaotic maps are non-convergent and highly sensitive to initial values. The applications include secure digital identity in distributed systems. Face and fingerprint biometric templates are subjected to hyper-chaotic map leading to encrypted image. Encrypted image is fed as an input to deoxyribonucleic acid (DNA) sequence. Dimensionality of generated DNA sequence is reduced by hashing. The intra-variation for a subject is measured with inter-quartile range. Image set with minimal variation value is identified for selecting the consistent image of a subject. 256 bit Key is generated from the consistent image. Generated key is reduced to 128 bits by eliminating subject specific outliers and redundant values. User specific features are extracted for both the traits using ResNet 50 convolutional neural network and are fused by addition. Final key is bound to feature vector by permutation function and time taken towards key binding is estimated with benchmark database SDUMLA-HMT. Outcome reveals that time taken for key binding varies between 45ms and 58ms for an image of size 80 MB.
