Lossless embedding: A visually meaningful image encryption algorithm based on hyperchaos and compressive sensing

doi:10.1088/1674-1056/aca149

Abstract A novel visually meaningful image encryption algorithm is proposed based on a hyperchaotic system and compressive sensing (CS), which aims to improve the visual security of steganographic image and decrypted quality. First, a dynamic spiral block scrambling is designed to encrypt the sparse matrix generated by performing discrete wavelet transform (DWT) on the plain image. Then, the encrypted image is compressed and quantified to obtain the noise-like cipher image. Then the cipher image is embedded into the alpha channel of the carrier image in portable network graphics (PNG) format to generate the visually meaningful steganographic image. In our scheme, the hyperchaotic Lorenz system controlled by the hash value of plain image is utilized to construct the scrambling matrix, the measurement matrix and the embedding matrix to achieve higher security. In addition, compared with other existing encryption algorithms, the proposed PNG-based embedding method can blindly extract the cipher image, thus effectively reducing the transmission cost and storage space. Finally, the experimental results indicate that the proposed encryption algorithm has very high visual security.

Keywords: chaotic image encryption compressive sensing meaningful cipher image portable network graphics image encryption algorithm

Received: 29 August 2022
Revised: 02 November 2022
Accepted manuscript online: 09 November 2022

PACS:	05.45.Gg	(Control of chaos, applications of chaos)
	07.05.Pj	(Image processing)
	05.45.Jn	(High-dimensional chaos)

Fund: Project supported by the National Natural Science Foundation of China (Grant No. 61672124), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (Grant No. MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (Grant No. XLYC1802013), Key R&D Projects of Liaoning Province (Grant No. 2019020105-JH2/103), Jinan City ‘20 Universities’ Funding Projects Introducing Innovation Team Program (Grant No. 2019GXRC031), and Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (Grant No. MIMS20-M-02).

Corresponding Authors: Lin Teng
E-mail: tenglin@dlmu.edu.cn

Cite this article:

Xing-Yuan Wang(王兴元), Xiao-Li Wang(王哓丽), Lin Teng(滕琳), Dong-Hua Jiang(蒋东华), and Yongjin Xian(咸永锦) Lossless embedding: A visually meaningful image encryption algorithm based on hyperchaos and compressive sensing 2023 Chin. Phys. B 32 020503

[1] Wang X Y and Liu P B 2022 IEEE Trans. Circuit. Syst. 69 1291
[2] Chen J J, Yan D W, Duan S K and Wang L D 2020 Chin. Phys. B 29 110504
[3] Yan X P, Wang X Y and Xian Y J 2022 Chin. Phys. B 31 080504
[4] Zhou N R, Yan X Y, Liang H R, Tao X Y and Li Y G 2018 Quantum Inf. Process. 17 338
[5] Yang Y G, Tian J, Lei H, Zhou Y H and Shi W M 2016 Inf. Sci. 345 257
[6] Fang P F, Liu H, Wu C M and Liu M 2022 Chin. Phys. B 31 040501
[7] Wang R, Li M Y and Luo H J 2022 Chin. Phys. B 31 080508
[8] Liu S T and Zhang L 2021 Surface Chaos and Its Applications (Singapore: Springer) pp. 30-32
[9] Xian Y J, Wang X Y and Teng L 2022 IEEE Trans. Circuit. Syst. Vid. 32 4028
[10] Xian Y J, Wang X Y, Wang X Y, Li Q and Yan X P 2022 IEEE Trans. Circuit. Syst. 69 3320
[11] Xian Y J, Wang X Y, Zhang Y Q, Wang X Y and Du X H 2021 Chin. Phys. B 30 060508
[12] Wen W Y, Wei K K, Zhang Y S, Fang Y M and Li M 2020 Nonlinear Dyn. 99 1587
[13] Chen J X and Zhou Y C 2020 Inf. Sci. 520 130
[14] Liu S T and Wang P 2018 Fractal Control Theory (Singapore: Springer Nature) pp. 97-111
[15] Liu S T, Zhang Y P and Liu C A 2020 Fractal Control and Its Applications (Switzerland: Springer Nature) pp. 61-80
[16] Liu S T, Wang Y P, Bi Z M and Wang Y 2021 Mathematical Principle and Fractal Analysis of Mesoscale Eddy (Singapore: Springer) pp. 121-125
[17] Li Q, Wang X Y, Ma B, Wang X Y, Wang C P, Gao S and Shi Y Q 2022 IEEE Trans. Circuit. Syst. Vid. 32 5695
[18] Shi H and Wang L D 2019 Acta Phys. Sin. 68 200501 (in Chinese)
[19] Wang X G, Li M, Yu N N, Xi S X, Wang X L and Lang L Y 2019 Acta Phys. Sin. 68 240503 (in Chinese)
[20] Kanso A and Ghebleh M 2017 Opt. Laser Eng. 90 196
[21] Kumar V and Kumar D 2017 Multimed. Tools Appl. 77 13279
[22] Wang X Y, Liu C and Jiang D H 2021 Inf. Sci. 574 505
[23] Wang X Y, Liu C and Jiang D H 2022 Inf. Sci. 610 300
[24] Armijo-Correa J O, Murguia J S, Mejia-Carlos M, Arce-Guevara V E and Aboytes-Gonzalez J A 2020 Opt. Laser Technol. 127 106165
[25] Bao L and Zhou Y C 2015 Inf. Sci. 324 197
[26] Chai X L, Gan Z H, Chen Y R and Zhang Y S 2017 Signal Process. 134 35
[27] Wang H, Xiao D, Li M, Xiang Y P and Li X Y 2019 Signal Process. 155 218
[28] Zhu L Y, Song H S, Zhang X, Yan M D, Zhang T, Wang X Y and Xu J 2020 Signal Process. 175 107629
[29] Hussain M, Wahab A W A, Ho A T S, Javed N and Jung K H 2017 Signal Process.-Image 50 44
[30] Tai W L, Yeh C M and Chang C C 2009 IEEE Trans. Circuit. Syst. Vid. 19 906
[31] Ping P, Fu J, Mao Y C, Xu F and Gao J 2019 IEEE Access 7 170168
[32] Ye G D, Pan C, Dong Y X, Jiao K X and Huang X L 2021 Trans. Emerg. Telecommun. Technol. 32 e4071
[33] Miri A and Faez K 2017 Multimed. Tools Appl. 77 13133
[34] Malik A, Wang X H, Chen T L, Yang T L, Khan A N, Wu H Z, Chen Y L and Hu Y 2019 J. Inf. Secur. Appl. 48 102374
[35] Wen W Y, Hong Y K, Feng Y M, Li M and Li M 2020 Signal Process. 173 107580
[36] Yang Y G, Zou L, Zhou Y H and Shi W M 2020 Optik 213 164422
[37] Wang X Y and Wang M J 2008 Physica A 387 3751
[38] Candes E J, Romberg J and Tao T 2006 IEEE Trans. Inf. Theory 52 489
[39] Donoho D L 2006 IEEE Trans. Inf. Theory 52 1289
[40] Musanna F, Dangwal D and Kumar S 2020 Multimed. Tools Appl. 79 25115
[41] Wang Z, Bovik C, Sheikh H R and Simoncelli E P 2004 IEEE Trans. Image Process. 13 600
[42] Alarez G and Li S J 2006 Int. J. Bifur. Chaos 16 2129
[43] Chai X L, Wu H Y, Gan Z H, Zhang Y S, Chen Y R and Nixon K W 2020 Opt. Laser Eng. 124 105837

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