UPSI Digital Repository (UDRep)
|
UPSI Digital Repository (UDRep)
|
|
|
| ||||||||||||||||||||||||||
| Abstract : Universiti Pendidikan Sultan Idris |
| Since the COVID-19 pandemic, telemedicine or non-face-to-face medicine has increased significantly. In practice, various types of medical images are essential to achieve effective telemedicine. Medical image encryption algorithms play an irreplaceable role in the fast and secure transmission and storage of these medical images. However, most of the existing medical image encryption algorithms are full encryption algorithms, which are inefficient and time-consuming, so they are not suitable for emergency medical scenarios. To improve the efficiency of encryption, a small number of works have focused on partial or selective encryption algorithms for medical images, in which different levels of encryption strategies were adopted for different information content regions of medical images. However, these encryption algorithms have inadequate security more or less. In this paper, based on the Logistic map, we designed an improved variable dimension map. Then, an encryption algorithm for medical images was proposed based on it. This algorithm has two modes: (1) full encryption mode and (2) semi-full encryption mode, which can better adapt to different medical scenarios, respectively. In full encryption mode, all pixels of medical images are encrypted by using the confusion-diffusion structure. In semi-full encryption mode, the region of interest of medical images is extracted. The confusion was first adopted to encrypt the region of interest, and then, the diffusion was adopted to encrypt the entire image. In addition, no matter which encryption mode is used, the algorithm provides the function of medical image integrity verification. The proposed algorithm was simulated and analyzed to evaluate its effectiveness. The results show that in semi-full encryption mode, the algorithm has good security performance and lower time consumption; while in full encryption mode, the algorithm has better security performance and is acceptable in time. Graphical Abstract: [Figure not available: see fulltext.] 2023, International Federation for Medical and Biological Engineering. |
| References |
Abd El-Latif AA, Abd-El-Atty B, Talha M (2017) Robust encryption of quantum medical images. IEEE Access 6:1073–1081. https://doi.org/10.1109/ACCESS.2017.2777869 Abdmouleh MK, Khalfallah A, Bouhlel MS (2017) A novel selective encryption DWT-based algorithm for medical image. In: 2017 14th International Conference on Computer Graphics, Imaging and Visualization, Marrakesh, Morocco, pp 79–84. https://doi.org/10.1109/CGiV.2017.10 Abdulbaqi AS, Obaid AJ, Mohammed AH (2021) ECG signals recruitment to implement a new technique for medical image encryption. J Discret Math Sci Crypt 24(6):1663–1673. https://doi.org/10.1080/09720529.2021.1884378 Akkasaligar PT, Biradar S (2020) Selective medical image encryption using DNA cryptography. Inf Secur J: Glob Perspect 29(2):91–101. https://doi.org/10.1080/19393555.2020. 1718248 Alvarez G, Li S (2006) Some basic cryptographic requirements for chaos-based cryptosystems. Int J Bifurcation Chaos 16(08):2129–2151 Aouissaoui I, Bakir T, Sakly A (2021) Robustly correlated key-medical image for DNA-chaos based encryption. IET Image Proc 15(12):2770–2786. https://doi.org/10.1049/ipr2. 12261 Arumugham S, Rajagopalan S, Bosco J, Rayappan B, Amirtharajan R (2018) Networked medical data sharing on secure medium–a web publishing mode for DICOM viewer with three layer authentication. J Biomed Inform 86:90–105. https://doi.org/10.1016/j.jbi.2018.08.010 Arunkumar S, Subramaniyaswamy V, Vijayakumar V, Chilamkurti N, Logesh R (2019) SVD-based robust image steganographic scheme using RIWT and DCT for secure transmission of medical images. Measurement 139:426–437. https://doi.org/10.1016/j.measurement.2019.02.069 Balasamy K, Suganyadevi S (2021) A fuzzy based ROI selection for encryption and watermarking in medical image using DWT and SVD. Multimed Tools Appl 80:7167–7186 Banday SA, Pandit MK (2021) Texture maps and chaotic maps framework for secure medical image transmission. Multimed Tools Appl 80(12):17667–17683 Banu SA, Amirtharajan R (2020) A robust medical image encryption in dual domain : chaos-DNA-IWT combined approach. Med Biol Eng Compu 58(7):1445–1458 Barik RC, Changder S (2021) A novel and efficient amino acid codon based medical image encryption scheme colligating multiple chaotic maps. Multimed Tools Appl 80:10723–10760 Belazi A, Talha M, Kharbech S, Xiang W (2019) Novel medical image encryption scheme based on chaos and DNA encoding. IEEE Access 7:36667–36681. https://doi.org/10.1109/ACCESS.2019.2906292 Chen M, Ma G, Tang C, Lei Z (2020) Generalized optical encryption framework based on shearlets for medical image. Opt Lasers Eng 128:106026. https://doi.org/10.1016/j.optla seng.2020.106026 Chen X, Hu C-J (2017) Medical image encryption based on multiple chaotic mapping and wavelet transform. Biomed Res 28(20):8834–8837 Chen X, Hu C (2017) Adaptive medical image encryption algorithm based on multiple chaotic mapping. Saudi J Biol Sci 24(8):1821–1827. https://doi.org/10.1016/j.sjbs.2017.11.023 Dagadu JC, Li J, Aboagye EO (2019) Medical image encryption based on hybrid chaotic DNA diffusion. Wireless Pers Commun 108(1):591–612. https://doi.org/10.1007/s11277-019-06420-z Dai Y, Wang H, Wang Y (2016) Chaotic medical image encryption algorithm based on bit-plane decomposition. Int J Pattern Recognit Artif Intell 30(4):1657001. https://doi.org/10.1142/S0218001416570019 Dai Y, Wang H, Zhou Z, Jin Z (2016) Research on medical image encryption in telemedicine systems. Technol Health Care 24(s2):S435–S442. https://doi.org/10.3233/THC-161166 Deb S, Bhuyan B (2021) Chaos-based medical image encryption scheme using special nonlinear filtering function based LFSR. Multimed Tools Appl 80(13):19803–19826 Elhoseny M, Shankar K, Lakshmanaprabu SK, Maseleno A, Arunkumar N (2020) Hybrid optimization with cryptography encryption for medical image security in Internet of Things. Neural Comput Appl 32:10979–10993. https://doi.org/10.1007/s00521-018-3801-x |
| This material may be protected under Copyright Act which governs the making of photocopies or reproductions of copyrighted materials. You may use the digitized material for private study, scholarship, or research. |