Please wait a minute...
Chin. Phys. B, 2023, Vol. 32(11): 114203    DOI: 10.1088/1674-1056/acef08
ELECTROMAGNETISM, OPTICS, ACOUSTICS, HEAT TRANSFER, CLASSICAL MECHANICS, AND FLUID DYNAMICS Prev   Next  

Optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system and compressed sensing

Yang Du(都洋)1, Guoqiang Long(隆国强)2, Donghua Jiang(蒋东华)3, Xiuli Chai(柴秀丽)2,†, and Junhe Han(韩俊鹤)1,‡
1 Center for Physics of Low-Dimensional Materials, Henan Joint International Research Laboratory of New Energy Materials and Devices, School of Physics and Electronics, Henan University, Kaifeng 475004, China;
2 School of Artificial Intelligence, Henan Engineering Research Center for Industrial Internet of Things, Henan University, Zhengzhou 450046, China;
3 School of Computer Science and Engineering, Sun Yat-sen University, Guangzhou 510006, China
Abstract  Some existing image encryption schemes use simple low-dimensional chaotic systems, which makes the algorithms insecure and vulnerable to brute force attacks and cracking. Some algorithms have issues such as weak correlation with plaintext images, poor image reconstruction quality, and low efficiency in transmission and storage. To solve these issues, this paper proposes an optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system (4D MHS) and compressed sensing (CS). Firstly, this paper proposes a new 4D MHS, which has larger key space, richer dynamic behavior, and more complex hyperchaotic characteristics. The introduction of CS can reduce the image size and the transmission burden of hardware devices. The introduction of double random phase encoding (DRPE) enables this algorithm has the ability of parallel data processing and multi-dimensional coding space, and the hyperchaotic characteristics of 4D MHS make up for the nonlinear deficiency of DRPE. Secondly, a construction method of the deterministic chaotic measurement matrix (DCMM) is proposed. Using DCMM can not only save a lot of transmission bandwidth and storage space, but also ensure good quality of reconstructed images. Thirdly, the confusion method and diffusion method proposed are related to plaintext images, which require both four hyperchaotic sequences of 4D MHS and row and column keys based on plaintext images. The generation process of hyperchaotic sequences is closely related to the hash value of plaintext images. Therefore, this algorithm has high sensitivity to plaintext images. The experimental testing and comparative analysis results show that proposed algorithm has good security and effectiveness.
Keywords:  memristor      hyperchaotic system      compressed sensing      fractional Fourier transform      optical image encryption  
Received:  30 May 2023      Revised:  13 July 2023      Accepted manuscript online:  11 August 2023
PACS:  42.30.-d (Imaging and optical processing)  
  42.30.Kq (Fourier optics)  
  42.30.Va (Image forming and processing)  
  42.30.Wb (Image reconstruction; tomography)  
Corresponding Authors:  Xiuli Chai, Junhe Han     E-mail:  chaixiuli@henu.edu.cn;junhh@henu.edu.cn

Cite this article: 

Yang Du(都洋), Guoqiang Long(隆国强), Donghua Jiang(蒋东华), Xiuli Chai(柴秀丽), and Junhe Han(韩俊鹤) Optical image encryption algorithm based on a new four-dimensional memristive hyperchaotic system and compressed sensing 2023 Chin. Phys. B 32 114203

[1] Yang Y, Cheng M, Ding Y and Zhang W 2023 IEEE Transactions on Services Computing 16 2387
[2] Jiang D, Njitacke Z T, De Dieu Nkapkop J, Tsafack N, Wang X and Awrejcewicz J 2023 IEEE Internet of Things Journal 10 7143
[3] Yu F, Kong X, Mokbel A A M, Yao W and Cai S 2023 IEEE Transactions on Circuits and Systems II:Express Briefs 70 326
[4] Su Y, Teng L, Liu P, Unar S, Wang X and Fu X 2023 IEEE Transactions on Circuits and Systems for Video Technology 33 4689
[5] Wang B, Song J, Li R, Han R, Zheng G and Yang H N 2019 Chin. Phys. B 29 014207
[6] Kong P, Wang B D, Wang P, Zivkovic V and Zhang J Q 2020 Chin. Phys. B 29 074201
[7] Chai X, Fu J, Gan Z, Lu Y and Zhang Y 2022 Nonlinear Dyn. 108 2671
[8] Cheng J, Yan X, Liu L, Jiang Y and Wang X 2022 Entropy 24 340
[9] Chai X, Wang Y, Chen X, Gan Z and Zhang Y 2022 IEEE Signal Processing Letters 29 972
[10] Fridrich J 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, 12-15 October 1997, pp. 1105-1110
[11] Wang X, Liu C and Zhang H 2016 Nonlinear Dyn. 84 1595
[12] Liu L and Miao S 2018 Multimedia Tools and Applications 77 21445
[13] Pak C and Huang L 2017 Signal Processing 138 129
[14] Wang S, Wang C and Xu C 2020 Optics and Lasers in Engineering 128 105995
[15] Zhou Y, Bao L and Chen C L P 2014 Signal Processing 97 172
[16] Seyedzadeh S M and Mirzakuchaki S 2012 Signal Processing 92 1202
[17] Hua Z, Fan Jin B X and Huang H 2018 Signal Processing 149 148
[18] Zhou M and Wang C 2020 Signal Processing 171 107484
[19] Li C, Li Z, Feng W, Tong Y, Du J and Wei D 2019 AEU-International Journal of Electronics and Communications 110 152861
[20] Wang Z, Min F and Wang E 2016 AIP Adv. 6 095316
[21] Ye X, Wang X, Gao S, Mou J, Wang Z and Yang F 2020 Nonlinear Dyn. 99 1489
[22] Peng G, Min F and Wang E 2018 Journal of Electrical and Computer Engineering 2018 8649294
[23] Donoho D L 2006 IEEE Transactions on Information Theory 52 1289
[24] Xu Q, Sun K, Cao C and Zhu C 2019 Optics and Lasers in Engineering 121 203
[25] Zhou N, Li H, Wang D, Pan S and Zhou Z 2015 Opt. Commun. 343 10
[26] Yang Y, Guan B, Li J, Li D, Zhou Y and Shi W 2019 Optics & Laser Technology 119 105661
[27] Zhou N, Pan S, Cheng S and Zhou Z 2016 Optics & Laser Technology 82 121
[28] Xu Q, Sun K, He S and Zhu C 2020 Optics and Lasers in Engineering 134 106178
[29] Huo D, Zhu Z, Wei L, Han C and Zhou X 2021 Opt. Commun. 492 126976
[30] Luo Y, Lin J, Liu J, Wei D, Cao L, Zhou R, Cao Y and Ding X 2019 Signal Processing 161 227
[31] Zhang B, Xiao D and Xiang Y 2021 IEEE Transactions on Multimedia 23 2656
[32] Shi H and Wang L D 2019 Acta Phys. Sin. 68 200501 (in Chinese)
[33] Guo Y, Chen W and Jing S W 2020 Chin. Phys. B 29 054203
[34] Wang L and Zhao S 2020 Chin. Phys. B 29 024204
[35] Refregier P and Javidi B 1995 Opt. Lett. 20 767
[36] Javidi B 1997 Phys. Today 50 27
[37] Chen L and Zhao D 2005 Opt. Commun. 254 361
[38] Zhao D, Li X and Chen L 2008 Opt. Commun. 281 5326
[39] Unnikrishnan G, Joseph J and Singh K 2000 Opt. Lett. 25 887
[40] Zhou N, Wang Y and Gong L 2011 Opt. Commun. 284 3234
[41] Liu Z, Zhang Y, Liu W, Meng F, Wu Q and Liu S 2013 Optics and Lasers in Engineering 51 967
[42] Chen J, Zhu Z, Fu C, Yu H and Zhang L 2015 Commun. Nonlinear Sci. Numer. Simul. 20 846
[43] Faragallah O S and Afifi A 2017 Opt. Quantum Electron. 49 89
[44] Zhang L, Zhou Y, Huo D, Li J and Zhou X 2018 Optics & Laser Technology 105 162
[45] Huo D, Zhou X, Zhang L, Zhou Y, Li H and Yi S 2018 J. Mod. Opt. 65 2093
[46] Xie Z L, Ma H T, Qi B, Ren G, Tan Y F, He B, Zeng H L and Jiang C 2015 Chin. Phys. Lett. 32 124203
[47] Xie Z L, Qi B, Ma H T, Ren G, Tan Y F, He B, Zeng H L and Jiang C 2016 Chin. Phys. Lett. 33 044206
[48] McBride A C and Kerr F H 1987 IMA J. Appl. Math. 39 159
[49] Hua Z, Zhu Z, Chen Y and Li Y 2021 Nonlinear Dyn. 104 4505
[50] Wu Y, Noonan J P and Agaian S 2011 IEEE International Conference on Systems, Man, and Cybernetics, 9-12 October 2011, pp. 3358-3364
[51] Chua L O and Sung Mo K 1976 Proc. IEEE 64 209
[52] Gan Z, Chai X, Zhang J, Zhang Y and Chen Y 2020 Neural Computing and Applications 32 14113
[53] Liang Y R and Xiao Z Y 2020 International Journal of Automation and Computing 17 292
[54] Zhu L, Song H, Zhang X, Yan M, Zhang L and Yan T 2019 IEEE Access 7 22161
[55] Fu J, Gan Z, Chai X and Lu Y 2022 Multimedia Tools and Applications 81 17401
[56] Lu Y, Gong M, Huang Z, Zhang J, Chai X and Zhou C 2022 Optik 263 169357
[1] Characteristic analysis of 5D symmetric Hamiltonian conservative hyperchaotic system with hidden multiple stability
Li-Lian Huang(黄丽莲), Yan-Hao Ma(马衍昊), and Chuang Li(李创). Chin. Phys. B, 2024, 33(1): 010503.
[2] Dynamical analysis, geometric control and digital hardware implementation of a complex-valued laser system with a locally active memristor
Yi-Qun Li(李逸群), Jian Liu(刘坚), Chun-Biao Li(李春彪), Zhi-Feng Hao(郝志峰), and Xiao-Tong Zhang(张晓彤). Chin. Phys. B, 2023, 32(8): 080503.
[3] Lightweight and highly robust memristor-based hybrid neural networks for electroencephalogram signal processing
Peiwen Tong(童霈文), Hui Xu(徐晖), Yi Sun(孙毅), Yongzhou Wang(汪泳州), Jie Peng(彭杰),Cen Liao(廖岑), Wei Wang(王伟), and Qingjiang Li(李清江). Chin. Phys. B, 2023, 32(7): 078505.
[4] A progressive surrogate gradient learning for memristive spiking neural network
Shu Wang(王姝), Tao Chen(陈涛), Yu Gong(龚钰), Fan Sun(孙帆), Si-Yuan Shen(申思远), Shu-Kai Duan(段书凯), and Li-Dan Wang(王丽丹). Chin. Phys. B, 2023, 32(6): 068704.
[5] Synchronization coexistence in a Rulkov neural network based on locally active discrete memristor
Ming-Lin Ma(马铭磷), Xiao-Hua Xie(谢小华), Yang Yang(杨阳), Zhi-Jun Li(李志军), and Yi-Chuang Sun(孙义闯). Chin. Phys. B, 2023, 32(5): 058701.
[6] Quantum entangled fractional Fourier transform based on the IWOP technique
Ke Zhang(张科), Lan-Lan Li(李兰兰), Pan-Pan Yu(余盼盼), Ying Zhou(周莹),Da-Wei Guo(郭大伟), and Hong-Yi Fan(范洪义). Chin. Phys. B, 2023, 32(4): 040302.
[7] Hopf bifurcation and phase synchronization in memristor-coupled Hindmarsh-Rose and FitzHugh-Nagumo neurons with two time delays
Zhan-Hong Guo(郭展宏), Zhi-Jun Li(李志军), Meng-Jiao Wang(王梦蛟), and Ming-Lin Ma(马铭磷). Chin. Phys. B, 2023, 32(3): 038701.
[8] Memristor's characteristics: From non-ideal to ideal
Fan Sun(孙帆), Jing Su(粟静), Jie Li(李杰), Shukai Duan(段书凯), and Xiaofang Hu(胡小方). Chin. Phys. B, 2023, 32(2): 028401.
[9] Single exposure passive three-dimensional information reconstruction based on an ordinary imaging system
Shen-Cheng Dou(窦申成), Fan Liu(刘璠), Hu Li(李虎), Xu-Ri Yao(姚旭日), Xue-Feng Liu(刘雪峰), and Guang-Jie Zhai(翟光杰). Chin. Phys. B, 2023, 32(11): 114204.
[10] Rucklidge-based memristive chaotic system: Dynamic analysis and image encryption
Can-Ling Jian(蹇璨岭), Ze-An Tian(田泽安), Bo Liang(梁波), Chen-Yang Hu(胡晨阳), Qiao Wang(王桥), and Jing-Xi Chen(陈靖翕). Chin. Phys. B, 2023, 32(10): 100503.
[11] High-performance artificial neurons based on Ag/MXene/GST/Pt threshold switching memristors
Xiao-Juan Lian(连晓娟), Jin-Ke Fu(付金科), Zhi-Xuan Gao(高志瑄),Shi-Pu Gu(顾世浦), and Lei Wang(王磊). Chin. Phys. B, 2023, 32(1): 017304.
[12] Firing activities in a fractional-order Hindmarsh-Rose neuron with multistable memristor as autapse
Zhi-Jun Li(李志军), Wen-Qiang Xie(谢文强), Jin-Fang Zeng(曾金芳), and Yi-Cheng Zeng(曾以成). Chin. Phys. B, 2023, 32(1): 010503.
[13] High throughput N-modular redundancy for error correction design of memristive stateful logic
Xi Zhu(朱熙), Hui Xu(徐晖), Weiping Yang(杨为平), Zhiwei Li(李智炜), Haijun Liu(刘海军), Sen Liu(刘森), Yinan Wang(王义楠), and Hongchang Long(龙泓昌). Chin. Phys. B, 2023, 32(1): 018502.
[14] Memristor hyperchaos in a generalized Kolmogorov-type system with extreme multistability
Xiaodong Jiao(焦晓东), Mingfeng Yuan(袁明峰), Jin Tao(陶金), Hao Sun(孙昊), Qinglin Sun(孙青林), and Zengqiang Chen(陈增强). Chin. Phys. B, 2023, 32(1): 010507.
[15] Pulse coding off-chip learning algorithm for memristive artificial neural network
Ming-Jian Guo(郭明健), Shu-Kai Duan(段书凯), and Li-Dan Wang(王丽丹). Chin. Phys. B, 2022, 31(7): 078702.
No Suggested Reading articles found!