Parallel remote sensing image encryption algorithm based on chaotic map and DNA encoding

Hui Zhou; Hongwei Xie; Hao Zhang; Huiting Zhang

doi:10.11834/jig.200344

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Parallel remote sensing image encryption algorithm based on chaotic map and DNA encoding
Vol. 26, Issue 5, Pages: 1081-1094(2021)
Received：01 July 2020，

Revised：2020-9-3，

Accepted：10 September 2020，

Published：16 May 2021
DOI： 10.11834/jig.200344
稿件说明：

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DOI：

Hui Zhou, Hongwei Xie, Hao Zhang, Huiting Zhang. Parallel remote sensing image encryption algorithm based on chaotic map and DNA encoding[J]. Journal of Image and Graphics, 2021, 26(5): 1081-1094. DOI： 10.11834/jig.200344.

摘要

目的

针对传统基于混沌系统的图像加密算法在加密遥感图像时存在速度差、安全性不足等问题，提出一种混沌系统和脱氧核糖核酸（deoxyribonucleic acid，DNA）编码的并行遥感图像加密算法，提升图像加密的效率和安全性。

方法

利用明文图像的安全散列算法256（secure Hash algorithm 256，SHA-256）哈希值修改混沌系统的参数和初始值，提高算法的明文敏感性，并通过2维Hénon-Sine映射置乱图像，打乱像素之间的分布规律；然后利用图形处理器（graphics processing unit，GPU）并行计算密钥序列，缩短加密时间，通过选择多个高维混沌系统和修改混沌系统初始值确保密钥序列的随机性；最后利用密钥序列和GPU对图像进行DNA并行加密，得到最终的密文图像。在DNA并行加密过程中，生成一种DNA-S盒，对DNA编码进行非线性替换。

结果

在遥感图像以及普通彩色图像上的仿真实验和安全性分析结果表明，本文算法在加密遥感图像上速度达到80 Mbit/s以上，密钥空间大于10

200

，信息熵趋近于8，密文图像直方图平坦均匀，且通过了美国国家标准与技术研究院（National Institute of Standards and Technology，NIST）随机测试以及卡方检验；与其他算法相比，本文算法在密钥空间、相邻像素相关性、像素改变率（number of changing pixel rate，NPCR）、统一平均变化强度（unified averaged changed intensity，UACI）和信息熵等评价指标上更接近理想值。

结论

本文算法在大幅提升加密速度的同时，保证算法足够安全，能够抵抗各种攻击，适合遥感图像以及大容量图像的保密存储和网络传输。

Abstract

Objective

Remote sensing technology has a wide range of applications in mineral resources

biological resources

environmental monitoring

disaster monitoring

etc. In Earth observation satellites

remote sensing images are subject to many accidental or malicious attacks

resulting in data loss and data integrity destruction. Because remote sensing images may contain confidential information

the safety of remote sensing images has received increasing attention. To solve this problem

an encryption algorithm is used to protect the image and prevent unauthorized access. In the past two decades

chaotic systems have been used as effective solutions for image encryption because of their good ergodicity

pseudo-randomness

initial condition sensitivity

and other properties. From the perspective of image encryption algorithms

various problems such as poor calculation speed and security problems exist. In traditional encryption algorithms based on chaotic technology

the length of the iterative key sequence is proportional to the size of the image

and the remote sensing image has a large capacity. Thus

encryption using chaotic systems

especially high-dimensional chaotic systems

will affect the encryption efficiency. Because deoxyribonucleic acid(DNA) encryption technology has the advantages of high parallelism

low power consumption

and high storage

it is usually combined with chaotic systems for image encryption. However

due to the limited DNA encoding and calculation rules

the encrypted image is still vulnerable. To further improve the encryption efficiency

some algorithms introduce the concept of parallelism into encryption algorithms; however

the current parallel encryption algorithm is mainly based on CPU parallelism and does not consider parallels in the calculation of key sequence. The number of parallels is limited by CPU threads

and it still cannot meet the efficiency requirements. To solve this problem

a graphics processing unit(GPU) parallel remote sensing image encryption algorithm is proposed

which improves the key sequence iteration method and encryption method and proposes a new DNA encoding substitution algorithm

thereby improving the security and efficiency of image encryption algorithms.

Method

First

the secure Hash algorithm 256 (SHA-256) Hash values of the plain image are used to modify the parameters and initial values of the chaotic system to improve the plain-image sensitivity of the algorithm. Then

two-dimensional Hénon-Sine mapping is used to complete the image scrambling

disturbing the distribution law between pixels; then

the GPU is used to calculate the key sequence in parallel to shorten the encryption time. Multiple chaos is selected

and the initial values of the chaotic system are modified to ensure the randomness of the key sequence. Finally

the key sequence is used to sequentially perform DNA encoding

substitution

addition

exclusive-OR

and decoding operations on the image to complete encryption. During this process

the DNA substitution is completed by the proposed DNA-S-box

which can be replaced nonlinearly. Due to the high degree of parallelism of the algorithm

GPU parallel encryption is used in the DNA encryption process to increase the encryption speed.

Result

Using three remote sensing images of the Landsat-8 satellite to analyze the encryption performance

the experimental results show that the correlation of the adjacent pixels of the remote sensing image encrypted using the algorithm of this study is infinitely close to 0

the information entropy is almost equal to the ideal value of 8

and the plain-image sensitivity is extremely high. The algorithm passed the National Institute of Standards and Technology(NIST) random test and chi-square test

indicating a very high-security performance. Moreover

the speed of the algorithm can reach 80 Mbit/s. The algorithm is used to encrypt the plain image of Lena and compare with other image encryption algorithms. The simulation results show that the key space

correlation of adjacent pixels

number of changing pixel rate(NPCR)

unified averaged changed intensity(UACI)

and information entropy of the proposed algorithm are closer to the ideal values.

Conclusion

This study proposes a remote sensing image encryption algorithm using GPU parallel

which improves the iterative chaotic sequence method and DNA encryption method

so that the encryption algorithm is suitable for GPU parallel computing

thereby increasing the speed of encryption and decryption while ensuring security. The simulation results show that the encryption algorithm has a larger key space

higher sensitivity in plain image

and faster speed compared with other algorithms. The proposed algorithm is suitable for military

medical

remote sensing

and other confidential images

especially large-capacity storage of confidential images and network transmission.

关键词

Keywords

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