Enhanced Arnold’s Cat Map-AES Encryption Technique for Medical Images

Mohamed A. Wahby Shalaby, Marwa T. Saleh, H. Elmahdy
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引用次数: 6

Abstract

Human’s health information is considered momentous information, which is represented in medical systems. The amount of medical image information available for analysis is increasing with the modern medical image devices and biomedical image processing techniques. To prevent data modification from unauthorized persons from an insecure network, medical images should be encrypted efficiently. In this paper, a novel chaotic-based medical image encryption technique is proposed. This technique uses first a Butterworth High Pass Filter (BHPF) to enhance the medical image’s details to avoid any possible loss of medical details during the encryption-decryption process. The proposed technique is then developed by modifying Arnold’s cat map technique combined with the well-known Advanced Encryption Standard (AES) algorithm. By modifying Arnold’s cat map technique, three bits are formulated and added to the regular AES encryption key to increase the overall encryption robustness. A comparative study is conducted to compare first the efficiency of the proposed technique concerning Arnold’s Cat Map with AES (Cat-AES) and AES in its standard form. Then, the proposed encryption technique is also compared to the state-of-the-art chaotic-based medical image encryption techniques. It is shown from the comparative study that the proposed approach is capable of increasing both the strength of the encryption/decryption process and the quality of medical images with a reduction of the overall computational cost.
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增强的Arnold Cat Map-AES医学图像加密技术
人体健康信息被认为是医疗系统中重要的信息。随着现代医学图像设备和生物医学图像处理技术的发展,可供分析的医学图像信息量不断增加。为了防止未经授权的人在不安全的网络中修改数据,医学图像必须进行有效的加密。提出了一种新的基于混沌的医学图像加密技术。该技术首先使用巴特沃斯高通滤波器(BHPF)增强医学图像的细节,以避免在加解密过程中可能丢失的医疗细节。然后,通过修改Arnold的猫图技术并结合著名的高级加密标准(AES)算法,开发了所提出的技术。通过修改Arnold的cat map技术,将三个比特添加到常规AES加密密钥中,以提高整体加密的鲁棒性。本文首先进行了一项比较研究,比较了所提出的关于Arnold’s Cat Map with AES (Cat-AES)和AES标准形式的效率。然后,将所提出的加密技术与最先进的基于混沌的医学图像加密技术进行了比较。对比研究表明,该方法能够提高加解密过程的强度和医学图像的质量,同时降低总体计算成本。
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