Abstract
To enhance the security of single-chaotic systems, we propose a novel image encryption cryptosystem based on true random numbers and chaotic systems. First, we select any one of several chaotic systems. Next, the hash function is used to calculate the initial value of the chaotic system using a plaintext image. Then, we obtain a solution of this chaotic system and use the k-medoids clustering machine-learning algorithm and chaotic sequence to scramble the original image. Finally, new random numbers obtained using a chaotic signal and true random numbers are used to perform the exclusive-OR operator on the scrambled results. To illustrate the effectiveness of our method, a one-dimensional (1D) logistic chaotic system is selected for image encryption. The simulation results show that compared with the existing models, such as image encryption based on chaos and image encryption based on the advanced encryption standar (AES), our method is simpler with a higher security and resists different classical attacks.






















Similar content being viewed by others
References
Kumar, K., Shrimankar, D.D.: F-DES: fast and deep event summarization. IEEE Trans. Multimedia 20(2), 323–334 (2017)
Manupriya, P., Sinha, S., Kumar, K.: V+see: video secret sharing encryption technique. In: 2017 conference on information and communication technology (CICT), pp. 1-6 (2017)
Kumar, K., Shrimankar, D.D., Singh, N.: Event bagging: a novel event summarization approach in multiview surveillance videos. 2017 International Conference on Innovations in Electronics, Signal Processing and Communication (IESC), pp. 106–111 (2017)
Atrish, A., Singh, N., Kumar, K., Kumar, V.: An automated hierarchical framework for player recognition in sports image. ICVIP 2017: Proceedings of the International Conference on Video and Image Processing, pp. 103–108 (2017)
Kumar, K., Shrimankar, D.D., Singh, N.: Somes: an efficient som technique for event summarization in multi-view surveillance videos. In: Sa P., Bakshi S., Hatzilygeroudis I., Sahoo M. (eds) Recent Findings in Intelligent Computing Techniques. Advances in Intelligent Systems and Computing, 709, Singapore, Springer, pp. 383–389 (2018)
Sharma, S., Kumar, K.: Guess: genetic uses in video encryption with secret sharing. In: Proceedings of 2nd Internationa l Conference on Computer Vision and Image Processing, pp 51–62 (2018)
Kumar, K., Shrimankar, D.D.: Deep event learning boost-up approach: delta. Multimed. Tools Appl. 77, 26635–26655 (2018)
Kumar, K., Shrimankar, D.D.: ESUMM: event summarization on scale-free networks. IETE Tech. Rev. 36(3), 1–10 (2018)
Kumar, K.: EVS-DK: event video skimming using deep keyframe. J. Vis. Commun. Image Represent. 58, 345–352 (2019)
Sharma, S., Shivhare, S.N., Singh, N., Kumar, K.: Computationally efficient ann model for small-scale problems. In: Tanveer, M., Pachori, R.B. (eds.) Machine intelligence and signal analysis, pp. 423–435. Springer, Singapore (2019)
Krishna, R., Kumar, K.: P-MEC: polynomial congruence based multimedia encryption technique over cloud. IEEE Consumer Electronics Magazine, Early Access (2020)
Sharma, S., Kumar, K., Singh, N.: Deep eigen space based ASL recognition system. IETE J. Res. 1–11 (2020)
Kumar, K.: Text query based summarized event searching interface system using deep learning over cloud. Multimed. Tools Appl. 6, 1–16 (2021)
Yan, C., Shao, B., Zhao, H., Ning, R., Zhang, Y., Xu, F.: 3D room layout estimation from a single RGB image. IEEE Trans. Multimed. 22(11), 3014–3024 (2020)
Yan, C., Li, Z., Zhang, Y., Liu, Y., Ji, X., Zhang, Y.: Depth image denoising using nuclear norm and learning graph model. ACM Trans. Multimed. Comput. Commun. Appl. 16(4), 1–17 (2020)
Yan, C., Gong, B., Wei, Y., Gao, Y.: Deep multi-view enhancement hashing for image retrieval. IEEE Trans. Pattern Anal. Mach. Intell. 43(4), 1445–1451 (2021)
Matthews, R.: On the derivation of a “chaotic” encryption algorithm. Cryptologia 13(1), 29–42 (1989)
Chen, G., Mao, Y., Chui, C. K.: A symmetric image encryption scheme based on 3D chaotic cat maps. Chaos Solitons Fract. 21(3), 749–761 (2004)
Yu, S.: Design principle of new chaotic circuits and systems and its applications. Science Press, Beijing (2016)
Hua, Z., Zhou, B., Zhou, Y.: Sine chaotification model for enhancing chaos and its hardware implementation. IEEE Trans. Industr. Electron. 66(2), 1273–1284 (2019)
Hua, Z., Zhou, Y., Bao, B.: Two-Dimensional sine chaotification system with hardware implementation. IEEE Trans. Industr. Inf. 16(2), 887–897 (2020)
Wang, X., Feng, L., Zhao, H.: Fast image encryption algorithm based on parallel computing system. Inf. Sci. 486, 340–358 (2019)
Wang, X., Li, Zhi: A color image encryption algorithm based on Hopfield chaotic neural network. Opt. Lasers Eng. 115, 107–118 (2019)
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)
Wang, X., Gao, S.: Image encryption algorithm based on the matrix semi-tensor product with a compound secret key produced by a Boolean network. Inf. Sci. 539, 195–214 (2020)
Zhou, S., Wang, X., Wang, M., Zhang, Y.: Simple colour image cryptosystem with very high level of security. Chaos Solitons Fract. 141, 110225 (2020)
Wang, M., Wang, X., Zhao, T., Zhang, C., Xia, Z., Yao, N.: Spatiotemporal Chaos in improved cross coupled map lattice and its application in a bit-level image encryption scheme. Inf. Sci. 544, 1–24 (2021)
Zhang, Y., Wang, X.: A symmetric image encryption algorithm based on mixed linear-nonlinear coupled map lattice. Inf. Sci. 273, 329–351 (2014)
Tong, X.: Design of an image encryption scheme based on a multiple chaotic map. Commun. Nonlinear Sci. Numer. Simul. 18(7), 1725–1733 (2013)
Natiq, H., Banerjee, S., Said, M.R.M.: Cosine chaotification technique to enhance chaos and complexity of discrete systems. Eur. Phys. Spec. Top. 228, 185–194 (2019)
Nepomuceno, E.G., Nardo, L.G., Arias-Garcia, J., Butusov, D. N., Tutueva, A.: Image encryption based on the pseudo-orbits from 1D chaotic map. Chaos 29, 061101 (2019)
Nardo, L.G., Nepomuceno, E.G., Arias-Garcia, J., Butusov, D.N.: Image encryption using finite-precision error. Chaos Solitons Fract. 123, 69–78 (2019)
Chen, C., Sun, K., He, S.: An improved image encryption algorithm with finite computing precision. Signal Process. 168, 107340 (2020)
Mansouri, A., Wang, X.: A novel one-dimensional sine powered chaotic map and its application in a new image encryption scheme. Inf. Sci. 520, 46–62 (2020)
Zhang, Y., Hao, J., Wang, X.: An efficient image encryption scheme based on s-boxes and fractional-order differential logistic map. IEEE Access 8, 54175–54188 (2020)
Xu, C., Sun, J., Wan, C.: An image encryption algorithm based on randomwalk and hyperchaotic systems. Int. J. Bifur. Chaos 30(4), 2050060 (2020)
Xie, E.Y., Li, C., Yu, S., Lu, J.: On the cryptanalysis of Fridrich’s chaotic image encryption scheme. Signal Process. 132, 150–154 (2016)
Chai, X., Chen, Y., Broyde, L.: A novel chaos-based image encryption algorithm using DNA sequence operations. Opt. Lasers Eng. 88, 197–213 (2017)
Liu, L., Liu, B., Hu, H., Miao, S.: Reducing the dynamical degradation by bi-coupling digital chaotic maps. Int. J. Bifur. Chaos 28(05), 1850059 (2018)
Ye, G., Pan, C., Dong, X., Shi, Y. & Huang, X.: Image encryption and hiding algorithm based on compressive sensing and random numbers insertion. Signal Process. 172, 107563 (2020)
Sheng, Z., Xie, S., Pan, C.: Probability and statistics. Higher Education Press, Beijing (2008)
May, B.R.: Simple mathematical models with very complicated dynamics. Nature 261, 459–467 (1976)
Wang, X., Gao, S., Ye, X., Zhou, S., Wang, M.: A new image encryption algorithm with cantor diagonal scrambling based on the PUMCML system. Int. J. Bifur. Chaos 31(1), 2150003 (2021)
Xu, Q., Sun, K., Zhu, C.: A visually secure asymmetric image encryption scheme based on RSA algorithm and hyperchaotic map. Phys. Scr. 95, 035223 (2020)
Zhang, Y.: The image encryption algorithm with plaintext-related shuffling. IETE Tech. Rev. 33(3), 310–322 (2015)
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)
Arab, A., Rostami, M.J., Ghavami, B.: An image encryption method based on chaos system and AES algorithm. J. Supercomput. 75, 6663–6682 (2019)
Shadangi, V., Choudhary, S.K., Patro, K.A.K., Acharya, B.: Novel arnold scrambling based CBC-AES image encryption. Int. J. Control Theory Appl. 10(15), 93–105 (2017)
Wu, Y., Noonan, J.P., Agaian, S.: NPCR and UACI randomness tests for imageencryption. Cyber J. Multidiscip. J. Sci. Technol. J. Select. Areas Telecommun. 1, 31–38 (2011)
Acknowledgements
This research is supported by the National Natural Science Foundation of China (No: 61672124), the Password Theory Project of the 13th Five-Year Plan National Cryptography Development Fund (No: MMJJ20170203), Liaoning Province Science and Technology Innovation Leading Talents Program Project (No: XLYC1802013), Key R&D Projects of Liaoning Province (No: 2019020105-JH2/103), Jinan City’20 universities’ Funding Projects Introducing Innovation Team Program (No: 2019GXRC031), Research Fund of Guangxi Key Lab of Multi-source Information Mining & Security (No: MIMS20-M-02), and the Scientific and Technological Research Program of Chongqing Municipal Education Commission (Nos: KJ1703056 and KJQN201900529).
Author information
Authors and Affiliations
Corresponding author
Additional information
Communicated by C. Yan.
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Zhou, S., Wang, X., Zhang, Y. et al. A novel image encryption cryptosystem based on true random numbers and chaotic systems. Multimedia Systems 28, 95–112 (2022). https://doi.org/10.1007/s00530-021-00803-8
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00530-021-00803-8