A Hyper-chaotic Medical Image Encryption with Optimized Key Value

PDF (2341KB), PP.18-34

Views: 0 Downloads: 0

Author(s)

Subhajit Das 1,* Manas Kumar Sanyal 1

1. University of Kalyani, West Bengal, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2024.03.02

Received: 10 Dec. 2023 / Revised: 14 Jan. 2024 / Accepted: 15 Mar. 2024 / Published: 8 Jun. 2024

Index Terms

Secret Key Value, Multipoint Crossover, Autonomous Hyper-chaotic, Optimization, Decryption Key

Abstract

This article delves into a medical image encryption/decryption method based on hyper chaotic dynamics and genetic algorithms. The proposed algorithm boasts simplicity in implementation, featuring straightforward operations that render it well-suited for real-time applications while elevating its security measures. Leveraging the sensitivity of chaotic behavior to initial conditions, a genetic algorithm is employed to select optimal initial conditions for the 5D multi-wing hyper-chaotic system. Initially, a secret key generation method based on the input image is applied, followed by stages of diffusion and encryption utilizing the chaotic system. The secret key undergoes optimization through a genetic algorithm, considering specific parameters within the encrypted image as encryption factors. Subsequently, the encrypted image with the optimized secret key is finalized, serving as the basis for decrypting the cipher image. The proposed method undergoes simulation, testing, and comparison against other image encryption algorithms. Both experimental results and computer simulations affirm the robustness of this cryptographic system, showcasing a significant key space value (2^256), high key sensitivity (Number of Pixels Change Rate: NPCR > 99.55%, Unified Average Changing Intensity: UACI > 33.37%), and its ability to fend off various types of attack.

Cite This Paper

Subhajit Das, Manas Kumar Sanyal, "A Hyper-chaotic Medical Image Encryption with Optimized Key Value", International Journal of Intelligent Systems and Applications(IJISA), Vol.16, No.3, pp.18-34, 2024. DOI:10.5815/ijisa.2024.03.02

Reference

[1]S. Ibrahim, Hesham Alhumyani, Mehedi Masud, Sultan S. Alshamrani, Omar Cheikhrouhou, Ghulam Muhammad, M. Shamim Hossain “Framework for efficient medical image encryption using dynamic S-boxes and chaotic maps”, IEEE Access, volume 8, pages 160433-160449,2020. 
[2]Zhongyun Hua, Shuang Yi, Yicong Zhou, “Medical image encryption using high-speed scrambling and pixel adaptive diffusion”, Signal Processing, volume 20, pp 134–144 ,2018.
[3]Weijia Cao, Yicong Zhou, C.L. Philip Chen, Liming Xia, “Medical image encryption using edge maps”. Signal Processing.  Volume 132, pp 96–109,2017.
[4]Chong Fu, Gao-yuan Zhang, Ou Bian, Wei-min Lei, Hong-feng Ma, “A novel medical image protection scheme using a 3-dimensional chaotic system”, PLoS One, volume 9, pp 1–25, 2014.
[5]Guodong Ye, Kaixin Jiao, Chen Pan, Xiaoling Huang, “An effective framework for chaotic image encryption based on 3D logistic map”, Security and Communication Networks, Volume2018, pp 1–11,2018.
[6]Y. Dai, X. Wang, “Medical image encryption based on a composition of Logistic maps and Chebyshev maps, 2012 IEEE International Conference on Information and Automation, Shenyang, China, pp 210-214 ,2012.
[7]Chong Fu, Wei-hong Meng, Yong-feng Zhan, Zhi-liang Zhu, Francis C.M.Lau ,Chi K.Tse ,Hong-feng Ma , “An efficient and secure medical image protection scheme based on chaotic maps”, Computers in Biology and Medicine  volume 43,issue 8 pages  1000–1010, 2013. https://doi.org/10.1016/j.compbiomed.2013.05.005
[8]Jun-xin Chen, Lei Chen, Leo Yu Zhang, Zhi-liang Zhu, “Medical image cipher using hierarchical diffusion and non-sequential encryption”, Nonlinear Dynamics 96, pp 301–322. 2019, doi:10.1007/s11071-019-04791-3.
[9]Yin Dai, Huanzhen Wang, Yuyi Wang, “Chaotic medical image encryption algorithm based on bit-plane decomposition”, International Journal of Pattern Recognition and Artificial Intelligence Volume 30, No. 4 1657001, 2016, https://doi.org/10.1142/S0218001416570019
[10]Xiao Chen,Chun Jie Hu, “Adaptive medical image encryption algorithm based on multiple chaotic mapping”, Saudi Journal of Biological Sciences, Volume 24, Issue 8,Pages 1821-1827,2017
[11]Li Huijuan, Wang Yurong, Zuo Zhengwei, “Chaos-based image encryption algorithm with orbit perturbation and dynamic state variable selection mechanisms”, Optics and Lasers in Engineering, Volume 115, pp 197-207,2019.
[12]Shanshan Li, Li Zhao, Na Yang, "Medical Image Encryption Based on 2D Zigzag Confusion and Dynamic Diffusion", Security and Communication Networks, vol. 2021, Article ID 6624809, 23 pages, 2021. https://doi.org/10.1155/2021/6624809. 
[13]Javan, A.A.K.; Jafari, M.; Shoeibi, A.; Zare, A.; Khodatars, M.; Ghassemi, N.; Alizadehsani, R.; Gorriz, J.M. “Medical Images Encryption Based on Adaptive-Robust Multi-Mode Synchronization of Chen Hyper-Chaotic Systems”. Sensors 2021, 21, 3925
[14]Liu, Shuang, Liu, Li, and Pang, Ming. “Encryption Method and Security Analysis of Medical Images Based on Stream Cipher Enhanced Logical Mapping” 1 pp 185 – 193, Jan. 2021.
[15]Hui Wang, Di Xiao, Xin Chen, Hongyu Huang, “Cryptanalysis and enhancements of image encryption using combination of the 1D chaotic map”, Signal Processing, Volume 144, pp 444-452, 2018, https://doi.org/10.1016/j.sigpro.2017.11.005
[16]Junxin Chen, Fangfang Han, Wei Qian, Yu-Dong Yao, Zhi-liang Zhu, “Cryptanalysis and improvement in an image encryption scheme using combination of the 1D chaotic map”, pNonlinear Dynamics 93,399–2413, 2018.  doi:10.1007/s11071-018-4332-9.
[17]Congxu Zhu, Guojun Wang, Kehui Sun, “Improved cryptanalysis and enhancements of an image encryption scheme using combined 1D chaotic maps”, Entropy 20 (11),843, 2018. 
[18]John H. Holland, Adaptation in natural and artificial Systems. “An introductory analysis with applications to biology, control, and artificial intelligence”, MIT Press, IEEE Explorer Online ISBN: 9780262275552. 
[19]A.E. Eiben, P-E. Raué, Zs. Ruttkay, “Genetic algorithms with multi-parent recombination. Proceedings of the 3rd conference on parallel problem solving from nature”, LNCS Series, Springer-Verlag, 1994
[20]Amin Zarei, “Complex dynamics in a 5-D hyper-chaotic attractor with four-wing, one equilibrium and multiple chaotic attractors”, Nonlinear Dynamics. ISSN 0924-090X, Volume 81, Combined 1-2, Nonlinear Dynamics ,2015 81:585-605, DOI 10.1007/s11071-015-2013-5
[21]Zhenjun Tang, Juan Song, Xianquan Zhang, Ronghai Sun, “Multiple-image encryption with bit-plane decomposition and chaotic maps, Optics and Lasers in Engineering,Volume 80, pp 1-11,2016, ISSN 0143-8166,https://doi.org/10.1016/j.optlaseng.2015.12.004.
[22]Seyed Mohammad Seyedzadeh, S. Mirzakuchaki, “A fast color image encryption algorithm based on coupled two-dimensional piecewise chaotic map”. Volume 92, Issue 5, pp 1202-1215,2012.
[23]Hongjuan Liu, Zhiliang Zhu, Huiyan Jiang, Beilei Wang, “A novel image encryption algorithm based on improved 3D chaotic cat map”, The 9th International Conference for Young Computer Scientists, Northeastern University, Shenyang, Liaoning, China, ICYCS 2008. 3016-3021. 10.1109/ICCIC.2010.5705910. 2008.
[24]Shun Zhang, Tiegang Gao, an image encryption scheme based on DNA coding, and permutation of hyper-image, Multimedia Tools and Applications. 75, pp 17157– 14170.201, doi: 10.1007/s11042-015-2982-
[25]V.Sangavi, P.Thangavel, “An exotic multi-dimensional conceptualization for medical image encryption exerting rossler system and Sine map”, Journal of Information Security and Applications, Volume 55,102626,ISSN 2214-2126,2020
[26]Manjit Kaur, Dilbag Singh, “Multi objective evolutionary optimization techniques based hyper chaotic map and their applications in image encryption”, Multidimensional Systems and Signal Processing 32(1), https://doi.org/10.1007/s11045-020-00739-8 ,2020
[27]Xiaodong Li,Cailan Zhou,Ning Xu, “A secure and efficient image encryption algorithm based on DNA coding and Spatiotemporal chaos”, International Journal of Network Security ,Volume 20,No 1,pp 110-120,2018
[28]Changjiang Zhu, Zhihua Gan, Yang Lu, Xiuli Chai, “An image encryption algorithm based on 3-D DNA level permutation and substitution scheme”, Multimedia Tools and Applications 79(4), pp 7227–7258, 2020. https://doi.org/10.1007/s11042-019-08226-4 
[29]Huijuan Li, Yurong Wang, Zheng-Wei Zuo, “Chaos-based image encryption algorithm with orbit perturbation and dynamic state variable selection mechanisms”, Optics and Lasers in Engineering, volume 115, pp 197–207.2019
[30]Hossein Nematzadeh, Rasul Enayatifar, Homayun Motameni, Frederico Gadelha Guimarães, Vitor Nazário Coelho, “Medical image encryption using a hybrid model of modified genetic algorithm and coupled map lattices”, Optics and Lasers in Engineering, volume 110, pages 24–32,2018
[31]Suresh N.Mali,Pradeep M.Patil ,Rajesh M.Jalnekar, “Robust and secured image-adaptive data hiding”, Digital Signal Processing. Volume 22, issue 2 pp 314–323. 2012
[32]Prema T, Akkasaligar, Sumangala Biradar, “Selective medical image encryption using DNA cryptography”. Information Security Journal,A Global Perspective. Volume 29, issue 2, pp 91-101,2020 10.1080/19393555.2020.1718248
[33]Joshua C. Dagadu, Jianping Li, Emelia O, Aboagye, Faith K Deynu, “Medical Image Encryption Scheme Based on Multiple Chaos and DNA coding”, International Journal of Network Security, Volume 21, No 1, pp 83-90,2019
[34]Belazi, Akram, Muhammad Talha, Sofiane Kharbech, Wei Xiang, “Novel medical image encryption scheme based on chaos, and DNA encoding”. IEEE Access. 7, pp 36667– 36681,2019 doi: 10.1109/ACCESS.2019.2906292
[35]Kiran, Parameshachari, “Selective image encryption of medical images based on threshold entropy and Arnold Cat map”, Bioscience Biotechnology Research Communications. Vol 13. pp 194-202,2020