Abstract
Data security and privacy are essential for transmitting, storing, and preserving medical images. This article provides a secure chaotic framework for medical image encryption. The suggested technique has two stages: bit-level permutation and 2D SIM-based diffusion. The lossless technique is recommended for medical image encryption and decryption. It addresses the limitations of low-dimensional chaotic maps, such as small intervals and few parameters, and medical images’ unique texture and form. The keyspace of the new method is sufficiently big, and the encryption and decryption procedures are key-sensitive. Simulations and testing validate the new algorithm’s effectiveness and efficiency. According to security assessments, the algorithm is resistant to common attacks. A comparison of several encryption methods is performed. The proposed encryption method surpasses current encryption techniques when it comes to encrypting medical images.
Supported by City University, Petaling Jaya, MALAYSIA.
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References
Alanezi, A., et al.: Securing digital images through simple permutation-substitution mechanism in cloud-based smart city environment. Secur. Commun. Netw. 2021 (2021). https://doi.org/10.1155/2021/6615512
Belazi, A., Talha, M., Kharbech, S., Xiang, W.: Novel medical image encryption scheme based on chaos and dna encoding. IEEE Access 7, 36667–36681 (2019). https://doi.org/10.1109/access.2019.2906292
Cao, W., Zhou, Y., Chen, C.P., Xia, L.: Medical image encryption using edge maps. Signal Process. 132, 96–109 (2017). https://doi.org/10.1016/j.sigpro.2016.10.003
Chen, J., Chen, L., Zhang, L.Y., Zhu, Z.: Medical image cipher using hierarchical diffusion and non-sequential encryption. Nonlinear Dyn. 96(1), 301–322 (2019). https://doi.org/10.1007/s11071-019-04791-3
Chen, M., Ma, G., Tang, C., Lei, Z.: Generalized optical encryption framework based on shearlets for medical image. Opt. Lasers Eng. 128, 106026 (2020). https://doi.org/10.1016/j.optlaseng.2020.106026
El-Latif, A.A.A., Abd-El-Atty, B., Belazi, A., Iliyasu, A.M.: Efficient chaos-based substitution-box and its application to image encryption. Electronics 10(12), 1392 (2021)
Gafsi, M., Abbassi, N., Hajjaji, M.A., Malek, J., Mtibaa, A.: Improved chaos-based cryptosystem for medical image encryption and decryption. Sci. Program. 2020 (2020). https://doi.org/10.1155/2020/6612390
Hafsa, A., Gafsi, M., Malek, J., Machhout, M.: Fpga implementation of improved security approach for medical image encryption and decryption. Sci. Program. 2021 (2021). https://doi.org/10.1155/2021/6610655
He, P., Sun, K., Zhu, C.: A novel image encryption algorithm based on the delayed maps and permutation-confusion-diffusion architecture. Secur. Commun. Netw. 2021 (2021). https://doi.org/10.1155/2021/6679288
Hua, Z., Yi, S., Zhou, Y.: Medical image encryption using high-speed scrambling and pixel adaptive diffusion. Signal Process. 144, 134–144 (2018). https://doi.org/10.1016/j.sigpro.2017.10.004
Joyia, G.J., Liaqat, R.M., Farooq, A., Rehman, S.: Internet of medical things (iomt): Applications, benefits and future challenges in healthcare domain. J. Commun. 12(4), 240–247 (2017)
Ke, G., Wang, H., Zhou, S., Zhang, H.: Encryption of medical image with most significant bit and high capacity in piecewise linear chaos graphics. Measurement 135, 385–391 (2019). https://doi.org/10.1016/j.measurement.2018.11.074
Koutras, D., Stergiopoulos, G., Dasaklis, T., Kotzanikolaou, P., Glynos, D., Douligeris, C.: Security in IOMT communications: a survey. Sensors 20(17), 4828 (2020)
Laiphrakpam, D.S., Khumanthem, M.S.: Medical image encryption based on improved elgamal encryption technique. Optik 147, 88–102 (2017). https://doi.org/10.1016/j.ijleo.2017.08.028
Liu, W., Sun, K., Zhu, C.: A fast image encryption algorithm based on chaotic map. Opt. Lasers Eng. 84, 26–36 (2016). https://doi.org/10.1016/j.optlaseng.2016.03.019
Liu, X., Xiao, D., Liu, C.: Quantum image encryption algorithm based on bit-plane permutation and sine logistic map. Quantum Inf. Process. 19(8), 1–23 (2020). https://doi.org/10.1007/s11128-020-02739-w
Mishra, Z., Acharya, B.: High throughput and low area architectures of secure iot algorithm for medical image encryption. J. Inf. Secur. Appl. 53, 102533 (2020). https://doi.org/10.1016/j.jisa.2020.102533
Shankar, K., Elhoseny, M., Chelvi, E.D., Lakshmanaprabu, S., Wu, W.: An efficient optimal key based chaos function for medical image security. IEEE Access 6, 77145–77154 (2018). https://doi.org/10.1109/access.2018.2874026
Tsafack, N., et al.: A memristive rlc oscillator dynamics applied to image encryption. J. Inf. Secur. Appl. 61, 102944 (2021)
Zhang, W.Z., et al.: Secure and optimized load balancing for multitier iot and edge-cloud computing systems. IEEE Internet Things J. 8(10), 8119–8132 (2020)
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Ravi, R.V., Goyal, S.B., Djeddi, C. (2022). A New Medical Image Encryption Algorithm for IoMT Applications. In: Djeddi, C., Siddiqi, I., Jamil, A., Ali Hameed, A., Kucuk, İ. (eds) Pattern Recognition and Artificial Intelligence. MedPRAI 2021. Communications in Computer and Information Science, vol 1543. Springer, Cham. https://doi.org/10.1007/978-3-031-04112-9_11
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