Bio-inspired cryptosystem on the reciprocal domain: DNA strands mutate to secure health data

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.

摘要

医疗保健和远程医疗行业依赖于互联网技术,数字健康数据更易受到网络攻击,因其中包含大量个人数据,因而,有必要保护数字医疗图像以及保证其安全传输。本文采用基于洛伦兹和吕混沌吸引子突变的DNA加密技术生成强伪随机密钥流。为增强混淆与扩散阶段的近似性系数,所提的混沌DNA加密系统在整数小波变换域和一个生物启发的交叉变异单元上运行。进而,使用组合演化吸引子中的量化混沌集进行异或运算。该算法可以获得平均信息熵7.9973,几乎接近于零相关性的像素变化率(number of pixel change rate, NPCR)99.642%,归一平均强度变化(unified average change in intensity, UACI)33.438%,以及密钥空间10²⁰³。此外,实验分析和基于美国国家标准与技术研究院(NIST)的统计测试套件测试证实,所提医疗图像加密技术具有抵御任何统计、差分和暴力攻击的能力。