×

A novel image encryption scheme with adaptive Fourier decomposition. (English) Zbl 1535.94015

Summary: This study creatively introduces a class of adaptive Fourier decomposition (AFD) techniques into the field of image encryption, where AFD and its variants are newly developed signal decomposition methods. The novelty of this article is twofold. First, we use three different AFD techniques, including Core AFD, Unwinding AFD, and Cyclic AFD, to generate two key streams through decomposing a source image. The two key streams generated by different AFD algorithms are different and aperiodic, which can effectively improve the security of encryption algorithm. Furthermore, this work also proposes a novel encryption method that implements the confusion and diffusion operations by index-sorted mapping method and pixel swapping operation based on two generated key streams, respectively. To ensure that the image is fully scrambled, both pixel-level and bit-level permutations are performed, which employs a novel bilateral sequence diffusion method to change the image pixel distribution based on pixel swap operations. The cryptographic performance of the scheme is evaluated through various security analyses, including key sensitivity, statistical, entropy, clipping attack, and differential attack analysis. Experimental results confirm that the proposed image encryption scheme ensures a high level of security and exhibits superior performance in resisting various attacks compared with several traditional and state-of-the-art image encryption methods.

MSC:

94A08 Image processing (compression, reconstruction, etc.) in information and communication theory
94A12 Signal theory (characterization, reconstruction, filtering, etc.)
94A60 Cryptography
42A38 Fourier and Fourier-Stieltjes transforms and other transforms of Fourier type
42C40 Nontrigonometric harmonic analysis involving wavelets and other special systems

Software:

iPrivacy
Full Text: DOI

References:

[1] Yu, J.; Zhang, B.; Kuang, Z.; Lin, D.; Fan, J., iPrivacy: Image privacy protection by identifying sensitive objects via deep multi-task learning, IEEE Trans. Inf. Forensics Secur., 12, 5, 1005-1016, 2016
[2] Çiftçi, S. S.; Akyüz, A. O.; Ebrahimi, T., A reliable and reversible image privacy protection based on false colors, IEEE Trans. Multimedia, 20, 1, 68-81, 2017
[3] Liu, X.; Wu, Y.; Zhang, H.; Wu, J.; Zhang, L., Quaternion discrete fractional Krawtchouk transform and its application in color image encryption and watermarking, Signal Process., 189, Article 108275 pp., 2021
[4] Tao, R.; Meng, X.-Y.; Wang, Y., Image encryption with multiorders of fractional Fourier transforms, IEEE Trans. Inf. Forensics Secur., 5, 4, 734-738, 2010
[5] Liu, X.; Han, G.; Wu, J.; Shao, Z.; Coatrieux, G.; Shu, H., Fractional Krawtchouk transform with an application to image watermarking, IEEE Trans. Signal Process., 65, 7, 1894-1908, 2017 · Zbl 1414.94019
[6] Hua, Z.; Liu, X.; Zheng, Y.; Yi, S.; Zhang, Y., Reversible data hiding over encrypted images via preprocessing-free matrix secret sharing, IEEE Trans. Circuits Syst. Video Technol., 1, 2023
[7] Shannon, C. E., Communication theory of secrecy systems, Bell Syst. Tech. J., 28, 4, 656-715, 1949 · Zbl 1200.94005
[8] Akhavan, A.; Samsudin, A.; Akhshani, A., A symmetric image encryption scheme based on combination of nonlinear chaotic maps, J. Franklin Inst. B, 348, 8, 1797-1813, 2011
[9] Zhang, Y.; Xiao, D.; Shu, Y.; Li, J., A novel image encryption scheme based on a linear hyperbolic chaotic system of partial differential equations, Signal Process.: Image Commun., 28, 3, 292-300, 2013
[10] Wang, X.; Gao, S., Application of matrix semi-tensor product in chaotic image encryption, J. Franklin Inst. B, 356, 18, 11638-11667, 2019 · Zbl 1455.94038
[11] Alawida, M.; Teh, J. S.; Mehmood, A.; Shoufan, A., A chaos-based block cipher based on an enhanced logistic map and simultaneous confusion-diffusion operations, J. King Saud Univ.-Comput. Inf. Sci., 34, 10, 8136-8151, 2022
[12] Toughi, S.; Fathi, M. H.; Sekhavat, Y. A., An image encryption scheme based on elliptic curve pseudo random and advanced encryption system, Signal Process., 141, 217-227, 2017
[13] Hayat, U.; Azam, N. A., A novel image encryption scheme based on an elliptic curve, Signal Process., 155, 391-402, 2019
[14] Banik, A.; Laiphrakpam, D. S.; Agrawal, A.; Patgiri, R., Secret image encryption based on chaotic system and elliptic curve cryptography, Digit. Signal Process., 129, Article 103639 pp., 2022
[15] Chen, J.; Zhu, Z.; Zhang, L.; Zhang, Y.; Yang, B., Exploiting self-adaptive permutation-diffusion and DNA random encoding for secure and efficient image encryption, Signal Process., 142, 340-353, 2018
[16] Chai, X.; Fu, X.; Gan, Z.; Lu, Y.; Chen, Y., A color image cryptosystem based on dynamic DNA encryption and chaos, Signal Process., 155, 44-62, 2019
[17] Wen, W.; Wei, K.; Zhang, Y.; Fang, Y.; Li, M., Colour light field image encryption based on DNA sequences and chaotic systems, Nonlinear Dynam., 99, 2, 1587-1600, 2020
[18] Jasra, B.; Moon, A. H., Color image encryption and authentication using dynamic DNA encoding and hyper chaotic system, Expert Syst. Appl., 206, Article 117861 pp., 2022
[19] Bhatnagar, G.; Wu, Q. J., Biometric inspired multimedia encryption based on dual parameter fractional fourier transform, IEEE Trans. Syst. Man Cybern.: Syst., 44, 9, 1234-1247, 2014
[20] Anand, A.; Singh, A. K., Joint watermarking-encryption-ECC for patient record security in wavelet domain, IEEE MultiMedia, 27, 3, 66-75, 2020
[21] Yang, Y.-G.; Tian, J.; Lei, H.; Zhou, Y.-H.; Shi, W.-M., Novel quantum image encryption using one-dimensional quantum cellular automata, Inform. Sci., 345, 257-270, 2016
[22] Dong, Y.; Zhao, G.; Ma, Y.; Pan, Z.; Wu, R., A novel image encryption scheme based on pseudo-random coupled map lattices with hybrid elementary cellular automata, Inform. Sci., 593, 121-154, 2022 · Zbl 1532.94041
[23] Lv, W.; Chen, J.; Chai, X.; Fu, C., A robustness-improved image encryption scheme utilizing life-liked cellular automaton, Nonlinear Dynam., 111, 4, 3887-3907, 2023
[24] Chai, X.; Zheng, X.; Gan, Z.; Han, D.; Chen, Y., An image encryption algorithm based on chaotic system and compressive sensing, Signal Process., 148, 124-144, 2018
[25] Nan, S.; Feng, X.; Wu, Y.; Zhang, H., Remote sensing image compression and encryption based on block compressive sensing and 2D-LCCCM, Nonlinear Dynam., 108, 3, 2705-2729, 2022
[26] Wang, X.; Gao, S., Image encryption algorithm for synchronously updating boolean networks based on matrix semi-tensor product theory, Inf. Sci., 507, 16-36, 2020 · Zbl 1456.68034
[27] Wen, W.; Hong, Y.; Fang, Y.; Li, M.; Li, M., A visually secure image encryption scheme based on semi-tensor product compressed sensing, Signal Process., 173, Article 107580 pp., 2020
[28] Zhang, Y.; Xiao, D., An image encryption scheme based on rotation matrix bit-level permutation and block diffusion, Commun. Nonlinear Sci. Numer. Simul., 19, 1, 74-82, 2014 · Zbl 1344.94015
[29] Zhou, Y.; Cao, W.; Chen, C. P., Image encryption using binary bitplane, Signal Process., 100, 197-207, 2014
[30] Souza, C. E.; Chaves, D. P.; Pimentel, C., One-dimensional pseudo-chaotic sequences based on the discrete arnold’s cat map over \(\mathbb{Z}_{3^m} \), IEEE Trans. Circuits Syst. II, 68, 1, 491-495, 2020
[31] Moon, S.; Baik, J.-J.; Seo, J. M., Chaos synchronization in generalized Lorenz systems and an application to image encryption, Commun. Nonlinear Sci. Numer. Simul., 96, Article 105708 pp., 2021 · Zbl 1462.37042
[32] Tong, X.; Cui, M., Image encryption scheme based on 3D baker with dynamical compound chaotic sequence cipher generator, Signal Process., 89, 4, 480-491, 2009 · Zbl 1157.94311
[33] Musanna, F.; Kumar, S., Image encryption using quantum 3-D Baker map and generalized gray code coupled with fractional Chen’s chaotic system, Quantum Inf. Process., 19, 8, 1-31, 2020 · Zbl 1508.81726
[34] Li, Z.; Peng, C.; Li, L.; Zhu, X., A novel plaintext-related image encryption scheme using hyper-chaotic system, Nonlinear Dynam., 94, 2, 1319-1333, 2018
[35] Wu, Y.; Zhang, L.; Qian, T.; Liu, X.; Xie, Q., Content-adaptive image encryption with partial unwinding decomposition, Signal Process., 181, Article 107911 pp., 2021
[36] Qian, T.; Zhang, L.; Li, Z., Algorithm of adaptive Fourier decomposition, IEEE Trans. Signal Process., 59, 12, 5899-5906, 2011 · Zbl 1393.94142
[37] Qian, T., Intrinsic mono-component decomposition of functions: An advance of Fourier theory, Math. Methods Appl. Sci., 33, 7, 880-891, 2010 · Zbl 1188.42001
[38] Qian, T., Adaptive Fourier decompositions and rational approximations, part I: Theory, Int. J. Wavelets Multiresolut. Inf. Process., 12, 05, Article 1461008 pp., 2014 · Zbl 1304.65283
[39] Qian, T., Cyclic AFD algorithm for the best rational approximation, Math. Methods Appl. Sci., 37, 6, 846-859, 2014 · Zbl 1287.42018
[40] Gao, Y.; Ku, M.; Qian, T.; Wang, J., FFT formulations of adaptive Fourier decomposition, J. Comput. Appl. Math., 324, 204-215, 2017 · Zbl 1369.65184
[41] Mi, W.; Qian, T.; Wan, F., A fast adaptive model reduction method based on Takenaka-Malmquist systems, Systems Control Lett., 61, 1, 223-230, 2012 · Zbl 1256.93029
[42] Chen, Q.; Qian, T.; Li, Y.; Mai, W.; Zhang, X., Adaptive Fourier tester for statistical estimation, Math. Methods Appl. Sci., 39, 12, 3478-3495, 2016 · Zbl 1357.62161
[43] Ma, J.; Zhang, T.; Dong, M., A novel ECG data compression method using adaptive fourier decomposition with security guarantee in e-health applications, IEEE J. Biomed. Health Inf., 19, 3, 986-994, 2014
[44] Tan, C.; Zhang, L.; t. Wu, H., A novel blaschke unwinding adaptive-Fourier-decomposition-based signal compression algorithm with application on ECG signals, IEEE J. Biomed. Health Inf., 23, 2, 672-682, 2019
[45] Wang, Z.; Wan, F.; Wong, C. M.; Zhang, L., Adaptive Fourier decomposition based ECG denoising, Comput. Biol. Med., 77, 195-205, 2016
[46] Garnett, J., Bounded Analytic Functions, 2007, Springer Science & Business Media
[47] Coifman, R. R.; Steinerberger, S.; Wu, H. T., Carrier frequencies, holomorphy, and unwinding, SIAM J. Math. Anal., 49, 6, 4838-4864, 2017 · Zbl 1384.30014
[48] Coifman, R. R.; Steinerberger, S., Nonlinear phase unwinding of functions, J. Fourier Anal. Appl., 23, 4, 778-809, 2017 · Zbl 1421.30002
[49] Hua, Z.; Zhou, Y., Image encryption using 2D Logistic-adjusted-Sine map, Inform. Sci., 339, 237-253, 2016
[50] Alawida, M.; Teh, J. S.; Samsudin, A.; Alshoura, W. H., An image encryption scheme based on hybridizing digital chaos and finite state machine, Signal Process., 164, 249-266, 2019
[51] Diab, H., An efficient chaotic image cryptosystem based on simultaneous permutation and diffusion operations, IEEE Access, 6, 42227-42244, 2018
[52] Alvarez, G.; Li, S., Some basic cryptographic requirements for chaos-based cryptosystems, Int. J. Bifurcation Chaos, 16, 08, 2129-2151, 2006 · Zbl 1192.94088
[53] Erkan, U.; Toktas, A.; Toktas, F.; Alenezi, F., 2D e \(\pi \)-map for image encryption, Inform. Sci., 589, 770-789, 2022 · Zbl 1536.94004
[54] Hua, Z.; Zhou, Y., Design of image cipher using block-based scrambling and image filtering, Inf. Sci., 396, 97-113, 2017 · Zbl 1454.94017
[55] Alawida, M.; Samsudin, A.; Teh, J. S.; Alkhawaldeh, R. S., A new hybrid digital chaotic system with applications in image encryption, Signal Process., 160, 45-58, 2019
[56] Xu, M.; Tian, Z., A novel image cipher based on 3D bit matrix and latin cubes, Inform. Sci., 478, 1-14, 2019
[57] Hua, Z.; Zhou, Y.; Huang, H., Cosine-transform-based chaotic system for image encryption, Inform. Sci., 480, 403-419, 2019
[58] Ravichandran, D.; Praveenkumar, P.; Rayappan, J. B.B.; Amirtharajan, R., DNA chaos blend to secure medical privacy, IEEE Trans. Nanobiosci., 16, 8, 850-858, 2017
[59] Cao, C.; Sun, K.; Liu, W., A novel bit-level image encryption algorithm based on 2D-LICM hyperchaotic map, Signal Process., 143, 122-133, 2018
[60] Zhou, Y.; Bao, L.; Chen, C. P., Image encryption using a new parametric switching chaotic system, Signal Process., 93, 11, 3039-3052, 2013
[61] Xian, Y.; Wang, X., Fractal sorting matrix and its application on chaotic image encryption, Inform. Sci., 547, 1154-1169, 2021 · Zbl 1479.94272
[62] Wu, Y.; Noonan, J. P.; Agaian, S., NPCR and UACI randomness tests for image encryption, Cyber J.: Multidiscip. J. Sci. Technol. J. Sel. Areas Telecommun. (JSAT), 1, 2, 31-38, 2011
[63] Himeur, Y.; Boukabou, A., A robust and secure key-frames based video watermarking system using chaotic encryption, Multimedia Tools Appl., 77, 7, 8603-8627, 2018
[64] Ping, P.; Xu, F.; Mao, Y.; Wang, Z., Designing permutation-substitution image encryption networks with henon map, Neurocomputing, 283, 53-63, 2018
[65] Hua, Z.; Jin, F.; Xu, B.; Huang, H., 2D logistic-sine-coupling map for image encryption, Signal Process., 149, 148-161, 2018
[66] Wang, X.; Feng, L.; Li, R.; Zhang, F., A fast image encryption algorithm based on non-adjacent dynamically coupled map lattice model, Nonlinear Dynam., 95, 4, 2797-2824, 2019 · Zbl 1439.94067
[67] Jithin, K.; Sankar, S., Colour image encryption algorithm combining Arnold map, DNA sequence operation, and a Mandelbrot set, J. Inf. Secur. Appl., 50, Article 102428 pp., 2020
[68] Xu, L.; Li, Z.; Li, J.; Hua, W., A novel bit-level image encryption algorithm based on chaotic maps, Opt. Lasers Eng., 78, 17-25, 2016
[69] Chai, X.; Chen, Y.; Broyde, L., A novel chaos-based image encryption algorithm using DNA sequence operations, Optics Lasers Eng., 88, 197-213, 2017
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. In some cases that data have been complemented/enhanced by data from zbMATH Open. This attempts to reflect the references listed in the original paper as accurately as possible without claiming completeness or a perfect matching.