Abbasi Saadullah Farooq, Ahmad Reehab, Mukherjee Teesta, Ding Xuefei, Bai Linxue, Pournik Omid, Arvanitis Theodoros N
Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham B15 2TT, United Kingdom.
Department of Biomedical Engineering, Riphah International University Islamabad, Pakistan.
Stud Health Technol Inform. 2025 Jun 26;328:268-272. doi: 10.3233/SHTI250717.
Over the past two decades, there has been a substantial increase in the use of the Internet of Medical Things (IoMT). In the smart healthcare setting, patients' data can be quickly collected, stored and processed through insecure medium such as the internet or cloud computing. To address this issue, researchers have developed a range of encryption algorithms to protect medical image data, however these remain vulnerable to brute force and differential cryptanalysis attacks by eavesdroppers. In this study, we propose an efficient approach to enhance the security of medical image transmission by transforming the ciphertext image into a visually meaningful image. The proposed algorithm uses a 3D hyperchaotic system to generate three chaotic sequences for permutation and diffusion, followed by the application of a substitution box (S Box) to increase redundancy. Additionally, the proposed study employed discrete wavelet transform (DWT) to transform ciphertext image into a visually meaningful image. This final image is not only secure but also improves its resistance to cyberattacks. The proposed encryption model demonstrates strong security performance, with key metrics including Unified Average Changing Intensity (UACI) of 36.17% and Number of Pixels Change Rate (NPCR) of 99.57%, highlighting its effectiveness in ensuring secure medical image transmission.
在过去二十年中,医疗物联网(IoMT)的使用大幅增加。在智能医疗环境中,患者数据可通过互联网或云计算等不安全媒介快速收集、存储和处理。为解决这一问题,研究人员开发了一系列加密算法来保护医学图像数据,但这些算法仍易受窃听者的暴力破解和差分密码分析攻击。在本研究中,我们提出一种有效方法,通过将密文图像转换为视觉上有意义的图像来增强医学图像传输的安全性。所提出的算法使用三维超混沌系统生成三个混沌序列用于置换和扩散,随后应用替换盒(S盒)以增加冗余度。此外,本研究采用离散小波变换(DWT)将密文图像转换为视觉上有意义的图像。最终图像不仅安全,而且提高了其对网络攻击的抵抗力。所提出的加密模型展示出强大的安全性能,关键指标包括统一平均变化强度(UACI)为36.17%,像素变化率数量(NPCR)为99.57%,突出了其在确保安全医学图像传输方面的有效性。