CLC number: TP309.7
On-line Access: 2021-07-20
Received: 2020-02-13
Revision Accepted: 2020-05-24
Crosschecked: 2021-06-16
Cited: 0
Clicked: 5649
Citations: Bibtex RefMan EndNote GB/T7714
S. Aashiq Banu, Rengarajan Amirtharajan. Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data[J]. Frontiers of Information Technology & Electronic Engineering, 2021, 22(7): 940-956.
@article{title="Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data",
author="S. Aashiq Banu, Rengarajan Amirtharajan",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="22",
number="7",
pages="940-956",
year="2021",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000071"
}
%0 Journal Article
%T Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data
%A S. Aashiq Banu
%A Rengarajan Amirtharajan
%J Frontiers of Information Technology & Electronic Engineering
%V 22
%N 7
%P 940-956
%@ 2095-9184
%D 2021
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000071
TY - JOUR
T1 - Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data
A1 - S. Aashiq Banu
A1 - Rengarajan Amirtharajan
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 22
IS - 7
SP - 940
EP - 956
%@ 2095-9184
Y1 - 2021
PB - Zhejiang University Press & Springer
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DOI - 10.1631/FITEE.2000071
Abstract: Healthcare and telemedicine industries are relying on technology that is connected to the Internet. Digital health data are more prone to cyber attacks because of the treasure trove of personal data they possess. This necessitates protection of digital medical images and their secure transmission. In this paper, an encryption technique based on DNA mutated with Lorenz and Lü chaotic attractors is employed to generate high pseudo-random key streams. The proposed chaos-DNA cryptic system operates on the integer wavelet transform (IWT) domain and a bio-inspired crossover, mutation unit for enhancing the confusion and diffusion phase in an approximation coefficient. Finally, an XOR operation is performed with a quantised chaotic set from the developed combined attractors. The algorithm attains an average entropy of 7.9973, near-zero correlation with an NPCR of 99.642%, a UACI of 33.438%, and a keyspace of 10203. Further, the experimental analyses and NIST statistical test suite have been designed such that the proposed medical image encryption technique has the potency to withstand any statistical, differential, and brute force attacks.
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