Full Text:   <2790>

Summary:  <1482>

CLC number: TP37

On-line Access: 2024-08-27

Received: 2023-10-17

Revision Accepted: 2024-05-08

Crosschecked: 2020-10-29

Cited: 0

Clicked: 5232

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Xiao-ling Huang

https://orcid.org/0000-0001-6129-1188

Guo-dong Ye

https://orcid.org/0000-0003-4222-1824

-   Go to

Article info.
Open peer comments

Frontiers of Information Technology & Electronic Engineering  2020 Vol.21 No.12 P.1783-1794

http://doi.org/10.1631/FITEE.2000241


Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform


Author(s):  Xiao-ling Huang, You-xia Dong, Kai-xin Jiao, Guo-dong Ye

Affiliation(s):  Faculty of Mathematics and Computer Science, Guangdong Ocean University, Zhanjiang 524088, China

Corresponding email(s):   guodongye@hotmail.com

Key Words:  Rivest-Shamir-Adleman (RSA), Arnold map, Pixel confusion, Asymmetric algorithm, Image confusion


Xiao-ling Huang, You-xia Dong, Kai-xin Jiao, Guo-dong Ye. Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(12): 1783-1794.

@article{title="Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform",
author="Xiao-ling Huang, You-xia Dong, Kai-xin Jiao, Guo-dong Ye",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="12",
pages="1783-1794",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2000241"
}

%0 Journal Article
%T Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform
%A Xiao-ling Huang
%A You-xia Dong
%A Kai-xin Jiao
%A Guo-dong Ye
%J Frontiers of Information Technology & Electronic Engineering
%V 21
%N 12
%P 1783-1794
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2000241

TY - JOUR
T1 - Asymmetric pixel confusion algorithm for images based on RSA and Arnold transform
A1 - Xiao-ling Huang
A1 - You-xia Dong
A1 - Kai-xin Jiao
A1 - Guo-dong Ye
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 12
SP - 1783
EP - 1794
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2000241


Abstract: 
We propose a new asymmetric pixel confusion algorithm for images based on the rivest-Shamir-Adleman (RSA) public-key cryptosystem and arnold map. First, the RSA asymmetric algorithm is used to generate two groups of Arnold transform parameters to address the problem of symmetrical distribution of arnold map parameters. Second, the image is divided into blocks, and the first group of parameters is used to perform Arnold confusion on each sub-block. Then, the second group of parameters is used to perform Arnold confusion on the entire image. The image correlation is thereby fully weakened, and the image confusion degree and effect are further enhanced. The experimental results show that the proposed image pixel confusion algorithm has better confusion effect than the classical arnold map based confusion and the row-column exchange based confusion. Specifically, the values of gray difference are close to one. In addition, the security of the new confusion operation is dependent on RSA, and it can act as one part of a confusion-substitution structure in a cipher.

基于RSA和Arnold变换的非对称图像混淆算法

黄小玲,董友霞,焦开心,叶国栋
广东海洋大学数学与计算机学院,中国湛江市,524088

摘要:提出一种新的基于Rivest-Shamir-Adleman(RSA)公钥密码系统和Arnold映射的非对称像素混淆算法。首先,为解决Arnold映射参数对称分布问题,采用RSA非对称算法生成两组Arnold映射变换参数。其次,将图像分成图像块,并利用第一组参数对各图像块进行Arnold混淆。然后,使用第二组参数对整个图像进行Arnold混淆。从而,充分削弱图像相关性,进一步提高图像混淆程度和效果。试验结果表明,相比于基于经典Arnold映射混淆和基于行列交换混淆,本文所提图像像素混淆算法具有更好混淆效果。具体来说,灰度差的值均接近于0。另外,新的混淆操作安全性依赖于RSA,可作为密码学中混淆-替换结构的一部分。

关键词:Rivest-Shamir-Adleman(RSA);Arnold映射;像素混淆;非对称算法;图像混淆

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

Reference

[1]Abbas NA, 2016. Image encryption based on independent component analysis and Arnold’s cat map. Egypt mboxInform J, 17(1):139-146.

[2]Arab A, Rostami MJ, Ghavami B, 2019. An image encryption method based on chaos system and AES algorithm. J Supercomput, 75(10):6663-6682.

[3]Boldyreva A, Imai H, Kobara K, 2010. How to strengthen the security of RSA-OAEP. IEEE Trans Inform Theory, 56(11):5876-5886.

[4]Chen JX, Zhu ZL, Zhang LB, et al., 2018. Exploiting self-adaptive permutation-diffusion and DNA random encoding for secure and efficient image encryption. Signal Process, 142:340-353.

[5]Chen LF, Zhao DM, Ge F, 2013. Image encryption based on singular value decomposition and Arnold transform in fractional domain. Opt Commun, 291:98-103.

[6]El-Khamy SE, Korany NO, El-Sherif MH, 2017. A security enhanced robust audio steganography algorithm for image hiding using sample comparison in discrete wavelet transform domain and RSA encryption. Multim Tool Appl, 76(22):24091-24106.

[7]Gan ZH, Chai XL, Han DJ, et al., 2019. A chaotic image encryption algorithm based on 3-D bit-plane permutation. Neur Comput Appl, 31(11):7111-7130.

[8]Gong LH, Qiu KD, Deng CZ, et al., 2019a. An image compression and encryption algorithm based on chaotic system and compressive sensing. Opt Laser Technol, 115:257-267.

[9]Gong LH, Qiu KD, Deng CZ, et al., 2019b. An optical image compression and encryption scheme based on compressive sensing and RSA algorithm. Opt Laser Eng, 121:169-180.

[10]Hua ZY, Xu BX, Jin F, et al., 2019. Image encryption using Josephus problem and filtering diffusion. IEEE Access, 7:8660-8674.

[11]Hui LCK, Lam KY, 1994. Fast square-and-multiply exponentiation for RSA. Electron Lett, 30(17):1396-1397.

[12]Khashan OA, Zin AM, Sundararajan EA, 2015. ImgFS: a transparent cryptography for stored images using a filesystem in userspace. Front Inform Technol Electron Eng, 16(1):28-42.

[13]Li P, Xu J, Mou J, et al., 2019. Fractional-order 4D hyperchaotic memristive system and application in color image encryption. EURASIP J Image Video Process, 2019:22.

[14]Liu LF, Hao SD, Lin J, et al., 2018. Image block encryption algorithm based on chaotic maps. IET Signal Process, 12(1):22-30.

[15]Liu ZJ, Gong M, Dou YK, et al., 2012. Double image encryption by using Arnold transform and discrete fractional angular transform. Opt Laser Eng, 50(2):248-255.

[16]Mansouri A, Wang XY, 2020. Image encryption using shuffled Arnold map and multiple values manipulations. Vis Comput.

[17]Méndez-Ramírez R, Arellano-Delgado A, Cruz-Hernández C, et al., 2018. Chaotic digital cryptosystem using serial peripheral interface protocol and its dsPIC implementation. Front Inform Technol Electron Eng, 19(2):165-179.

[18]Mitchell CJ, 2016. On the security of 2-key triple DES. IEEE Trans Inform Theory, 62(11):6260-6267.

[19]Mossa E, 2017. Security enhancement for AES encrypted speech in communications. Int J Speech Technol, 20(1):163-169.

[20]Patidar V, Pareek NK, Purohit G, et al., 2011. A robust and secure chaotic standard map based pseudorandom permutation-substitution scheme for image encryption. Opt Commun, 284(19):4331-4339.

[21]Rawat N, Kim B, Kumar R, 2016. Fast digital image encryption based on compressive sensing using structurally random matrices and Arnold transform technique. Optik, 127(4):2282-2286.

[22]Sneha PS, Sankar S, Kumar AS, 2020. A chaotic colour image encryption scheme combining Walsh-Hadamard transform and Arnold-Tent maps. J Amb Intell Human Comput, 11(3):1289-1308.

[23]Verma G, Liao MH, Lu DJ, et al., 2019. An optical asymmetric encryption scheme with biometric keys. Opt Laser Eng, 116:32-40.

[24]Wu C, Hu LY, Wang Y, et al., 2019. Scalable asymmetric image encryption based on phase-truncation in cylindrical diffraction domain. Opt Commun, 448:26-32.

[25]Xiao D, Wang Y, Xiang T, et al., 2017. High-payload completely reversible data hiding in encrypted images by an interpolation technique. Front Inform Technol Electron Eng, 18(11):1732-1743.

[26]Yao LL, Yuan CJ, Qiang JJ, et al., 2017. An asymmetric color image encryption method by using deduced gyrator transform. Opt Laser Eng, 89:72-79.

[27]Ye GD, 2010. Image scrambling encryption algorithm of pixel bit based on chaos map. Patt Recogn Lett, 31(5):347-354.

[28]Ye GD, Huang XL, 2018. Spatial image encryption algorithm based on chaotic map and pixel frequency. Sci China Inform Sci, 61(5):058104.

[29]Ye GD, Pan C, Huang XL, et al., 2018. An efficient pixel-level chaotic image encryption algorithm. Nonl Dynam, 94(1):745-756.

[30]Yu SS, Zhou NR, Gong LH, et al., 2020. Optical image encryption algorithm based on phase-truncated short-time fractional Fourier transform and hyper-chaotic system. Opt Laser Eng, 124:105816.

[31]Zhou NR, Zhang AD, Zheng F, et al., 2014. Novel image compression-encryption hybrid algorithm based on key-controlled measurement matrix in compressive sensing. Opt Laser Technol, 62:152-160.

[32]Zhou NR, Hua TX, Gong LH, et al., 2015. Quantum image encryption based on generalized Arnold transform and double random-phase encoding. Quant Inform Process, 14(4):1193-1213.

[33]Zhu HH, Chen XB, Yang YX, 2019. A quantum image dual-scrambling encryption scheme based on random permutation. Sci China Inform Sci, 62(12):229501.

[34]Zhu ZL, Zhang W, Wong KW, et al., 2011. A chaos-based symmetric image encryption scheme using a bit-level permutation. Inform Sci, 181(6):1171-1186.

Open peer comments: Debate/Discuss/Question/Opinion

<1>

Please provide your name, email address and a comment





Journal of Zhejiang University-SCIENCE, 38 Zheda Road, Hangzhou 310027, China
Tel: +86-571-87952783; E-mail: cjzhang@zju.edu.cn
Copyright © 2000 - 2024 Journal of Zhejiang University-SCIENCE