Abstract
In this paper, a new two-dimensional discrete hyperchaotic system is proposed. Verification using the phase-track map, bifurcation map and Lyapunov exponent of the chaotic system shows that the chaotic system has better traversal, hyperchaos, unpredictability and wider chaotic region compared with the existing two-dimensional discrete chaotic systems. To improve the efficiency and security of the image encryption algorithm, this paper firstly uses parallel compressive sensing-aware image processing to greatly improve the efficiency of the image encryption. Secondly, index scrambling and forward and backward diffusion using a combination of a subset of discrete data sequences generated by a two-dimensional discrete hyperchaotic system improves the security of the image encryption algorithm. In addition ,the initial key and the sum of some pixel values of the original image are used to generate the initial values and control parameters of the 2D-SLS chaotic sequence using the hash of SHA-512, making the proposed algorithm robust to known plaintext and selected plaintext attacks. Simulation and experimental results show that the proposed algorithm is more efficient and secure than recently proposed encryption algorithms.












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References
Ajagbe SA, Adesina AO (2020) Design and development of an access control based electronic medical record (emr). CPJ 26:98–119
Liu JY, Yang DD, Zhou HB, Chen SQ (2018) A digital image encryption algorithm based on bit-planes and an improved logistic map. Multimed Tools Appl 77:10217–10233. https://doi.org/10.1007/s11042-017-5406-2
Liu GZ,Wu Q,Wang GY,Jin PP (2022) A improved logistic chaotic map and its application to image encryption and hiding. J Electron Inf Technol 44:3602–3609. https://doi.org/10.11999/JEIT210763
Li CL,Zhou Y,Li HM ,Feng W, Du JR (2021) Image encryption scheme with bit-level scrambling and multiplication diffusion. Multimed Tools Appl 80:18479 – 18501. https://doi.org/10.1007/s11042-021-10631-7
Wu WS, Wang GY,Wu Q (2023) Image encryption based on improved two-dimensional mapping and dna coding. J Hangzhou Dianzi Univ (Nat Sci) 43:34–4048
Deng WB, Liu S, Liu FC, Huang RN (2022) An image encryption algorithm based on compressed sensing and DNA coding. Comput Eng Sci 44(9):1574–1582
Wu XG,Wang KS,Wang XY, KanHB, Jürgen Kurths (2018) Color image dna encryption using nca map-based cml and one-time keys. Signal Proc 148(jul.):272–287. https://doi.org/10.1016/j.sigpro.2018.02.028
Dong WL, Li QL, Tang YW, Hu M, Zeng R (2021) A robust and multi chaotic DNA image encryption with pixel-value pseudorandom substitution scheme. Opt Commun 499(127):211. https://doi.org/10.1016/j.optcom.2021.127211
Yousif SF, Abboud AJ, Alhumaima RS (2022) A new image encryption based on bit replacing, chaos and DNA coding techniques. Multimedia Tools Appl 81:27453–27493. https://doi.org/10.1007/s11042-022-12762-x
Brahim Anis Bacha Bel Hadj, NHs Adda Ali Pacha, (2023) A new image compression-encryption scheme based on compressive sensing & classical AES algorithm. Multimed Tools Appl 1–31. https://doi.org/10.1007/s11042-023-15171-w
Hafsa A, Sghaier A, Malek J, Machhout M (2021) Image encryption method based on improved ecc and modified AES algorithm. Multimed Tools Appl 80:19769–19801. https://doi.org/10.1007/s11042-021-10700-x
Sun FY, Lv ZB (2021) A secure image encryption based on spatial surface chaotic system and AES algorithm. Multimed Tools Appl 81:3959–3979. https://doi.org/10.1007/s11042-021-11690-6
Jiang DH, Zhu LY, Shen ZY, Wang XY, Chen YP (2022) A double image visual security encryption algorithm combining 2d compressive sensing and chaotic mapping. J Xi’an Jiaotong Univ 56(002):140–148
Wang XY, Liu C, Jiang DH (2021) A novel triple-image encryption and hiding algorithm based on chaos, compressive sensing and 3d DCT. Inf Sci 574:505–527. https://doi.org/10.1016/j.ins.2021.06.032
Hua ZY, Zhou YC, Huang HJ (2019) Cosine-transform-based chaotic system for image encryption. Inf Sci Int J 480:403–419. https://doi.org/10.1016/j.ins.2018.12.048
Mansouri Ali, Wang XY (2020) A novel one-dimensional sine powered chaotic map and its application in a new image encryption scheme. Inf Sci 520:46–62. https://doi.org/10.1016/j.ins.2020.02.008
Tang ZJ, Yang Y, Xu SJ, Yu CQ, Zhang XQ et al (2019) Image encryption with double spiral scans and chaotic maps. Secur Commun Netw 2019. https://doi.org/10.1155/2019/8694678
Tang ZJ, Wang F, Zhang XQ (2017) Image encryption based on random projection partition and chaotic system. Multimed Tools Appl 76:8257–8283. https://doi.org/10.1007/s11042-016-3476-1
Hua ZY, Zhou YC (2016) Image encryption using 2d logistic-adjusted-sine map. Inf Sci 339:237–253. https://doi.org/10.1016/j.ins.2016.01.017
Liu SC ,Li CB,Li YX (2022) A novel image encryption algorithm based on exponent-cosine chaotic mapping. J Electron Inf Technol 44(5):1754–1762. https://doi.org/10.11999/JEIT210270
Chen S, Lü J, (2002) Parameters identification and synchronization of chaotic systems based upon adaptive control. Phys Lett A 299(4):353–358. https://doi.org/10.1016/S0375-9601(02)00522-4
Ye GD (2010) Image scrambling encryption algorithm of pixel bit based on chaos map. Pattern Recogn Lett 31(5):347–354. https://doi.org/10.1016/j.patrec.2009.11.008
Donoho D (2006) Compressed sensing. IEEE Trans Inf Theory 52(4):1289–1306. https://doi.org/10.1109/TIT.2006.871582
Shi H, Wang LD (2019) Multi-process image encryption scheme based on compressed sensing and multi-dimensional chaotic system*. Acta PhysSin 68(20):39–52. https://doi.org/10.7498/aps.68.20190553
Gong LH, Qiu KD, Deng CW, Zhou NR (2019) An image compression and encryption algorithm based on chaotic system and compressive sensing. Opt Laser Technol 115:257–267. https://doi.org/10.1016/j.optlastec.2019.01.039
Hua ZY, Zhang KY, Li YM, Zhou YC (2021) Visually secure image encryption using adaptive-thresholding sparsification and parallel compressive sensing. Signal Process 183(107):998. https://doi.org/10.1016/j.sigpro.2021.107998
HY W, Vieira J (2010) 2-d wavelet transforms in the form of matrices and application in compressed sensing. 2010 8th World Congress on Intelligent Control and Automation
Fay R, Ruland C (2016) Compressive sensing encryption modes and their security. 2016 11th International Conference for Internet Technology and Secured Transactions (ICITST)
Cai J, Xie SC, Zhang JZ (2023) Image compression-encryption algorithm based on chaos and compressive sensing. Multimed Tools Appl 82(14):22189–22212. https://doi.org/10.1007/s11042-022-13346-5
Wang ZP, Jiang YN, Chen SF (2022) Image parallel block compressive sensing scheme using DFT measurement matrix. Multimed Tools Appl 82:21561–21583. https://doi.org/10.1007/s11042-022-14176-1
Sun KH (2015) Principle and technology of chaotic secure communication. Tsinghua University Press, BeiJing
Candes EJ, Tao T (2005) Decoding by linear programming. IEEE Trans Inf Theory 51(12):4203–4215. https://doi.org/10.1109/TIT.2005.858979
Pati Y, Rezaiifar R, Krishnaprasad P (1993) Orthogonal matching pursuit: recursive function approximation with applications to wavelet decomposition. In: Proceedings of 27th Asilomar Conference on Signals, Systems and Computers
Dai W, Milenkovic O (2008) Subspace pursuit for compressive sensing signal reconstruction. IEEE Trans Inf Theory 55(5):2230–2249. https://doi.org/10.1109/TIT.2009.2016006
Mohimani GH, Babaie-Zadeh M, Jutten C (2007) Fast sparse representation based on smoothed 0 norm. In: International Conference on Independent Component Analysis & Signal Separation, pp 389–396
Alvarez G, Li S (2006) Some basic cryptographic requirements for chaos-based cryptosystems. Int J Bifurcation Chaos Appl Sci Eng 16:2129–2151. https://doi.org/10.1142/S0218127406015970
Wei DYJM (2021) A fast image encryption algorithm based on parallel compressive sensing and DNA sequence. Opt - Int J Light Electron Opt 238(6):166748. https://doi.org/10.1016/j.ijleo.2021.166748
Musanna F, Kumar S (2020) A novel image encryption algorithm using chaotic compressive sensing and nonlinear exponential function. J Inf Secur Appl 54:102560. https://doi.org/10.1016/j.jisa.2020.102560
Zhou KL, Fan JJ, Fan HJ, Li M (2020) Secure image encryption scheme using double random-phase encoding and compressed sensing. Opt Laser Technol 121:105769–105769. https://doi.org/10.1016/j.optlastec.2019.105769
Xu QY, Sun KH, He SB, Zhu CX (2020) An effective image encryption algorithm based on compressive sensing and 2d-slim. Opt Lasers Eng 134:106178. https://doi.org/10.1016/j.optlaseng.2020.106178
Liu JL, Zhang M, Tong X, Wang Z (2021) Image compression and encryption algorithm based on compressive sensing and nonlinear diffusion. Multimed Tools Appl 80(17):25433–25452. https://doi.org/10.1007/s11042-021-10884-2
Liang F, Li Y, Chen CH, Ye ZY, Zhou JT (2017) Ossim:an object-based multiview stereo algorithm using ssim index matching cost. IEEE Trans Geoence Remote Sens 55(12):6937–6949. https://doi.org/10.1109/TGRS.2017.2737033
Xu J, Mou J, Liu J, Hao J (2022) The image compression-encryption algorithm based on the compression sensing and fractional-order chaotic system. Vis Comput 38:1509–1526. https://doi.org/10.1007/s00371-021-02085-7
Gan ZH, Chai XL, Zhang JT, Zhang YS, Chen YR (2020) An effective image compression-encryption scheme based on compressive sensing (CS) and game of life (gol). Neural Comput & Applic 32:14113–14141. https://doi.org/10.1007/s00521-020-04808-8
Xu QY, Sun KH, He SB, Zhu CX (2020) An effective image encryption algorithm based on compressive sensing and 2d-slim. Optics Lasers Eng 134(106):178. https://doi.org/10.1016/j.optlaseng.2020.106178
Chai XL, Zheng XY, Gan ZH, Han DJ, Chen YR (2018) An image encryption algorithm based on chaotic system and compressive sensing. Signal Process 148:124–144. https://doi.org/10.1016/j.sigpro.2018.02.007
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Gao, Y., Liu, J. & Chen, S. Image encryption algorithms based on two-dimensional discrete hyperchaotic systems and parallel compressive sensing. Multimed Tools Appl 83, 57139–57161 (2024). https://doi.org/10.1007/s11042-023-17745-0
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DOI: https://doi.org/10.1007/s11042-023-17745-0