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Texture maps and chaotic maps framework for secure medical image transmission

机译:安全医学图像传输的纹理地图和混沌地图框架

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摘要

Telemedicine has evolved significantly for detection and diagnosis of diseases remotely, which means more frequent transmission of medical images over the network. The security of any medical image can be characterized as its integrity, confidentiality and authentication. It is these security vulnerabilities that limit the development of mobile healthcare applications, which intend to improve the efficiency of medical image communication. To address the vulnerabilities associated with medical images, we propose a texture edge map and multilevel chaotic map driven encryption framework for medical images. This technique utilizes texture maps generated by utilizing a bank of gabor filters along with multiple chaotic maps viz.: Sine, Cubic and Logistic maps for enhancing the key space, robustness and security of medical images over an insecure channel. The security, speed and reliability of the proposed technique for medical images are illustrated via experiments for key sensitivity, statistical and performance analysis. The proposed technique offers a large key space, pixel diffusion at an acceptable speed. Security analysis shows a high sensitive dependence of the encryption and decryption techniques to any subtle change in the secret key, the plain medical image and the encrypted image. Also, the proposed technique has a large enough key space to see off brute force attacks. Therefore, the proposed technique is a potential candidate for addressing security vulnerabilities of medical images over the communication networks.
机译:远程医疗在远程检测和诊断疾病的检测和诊断方面已经显着演变,这意味着在网络上更频繁地传播医学图像。任何医学图像的安全性都可以表征为其完整性,机密性和认证。这是这些安全漏洞,限制了移动医疗保健应用的发展,该应用程序打算提高医学图像通信的效率。要解决与医学图像相关的漏洞,我们提出了一个纹理边缘地图和多级混沌映射驱动的医学图像加密框架。该技术利用通过利用Gabor滤波器的银行以及多个混沌映射viz而生成的纹理映射:正弦,立方和逻辑图,用于在不安全的频道上增强医学图像的关键空间,鲁棒性和安全性。通过实验来说明所提出的医学图像技术的安全性,速度和可靠性,以进行关键灵敏度,统计和性能分析。所提出的技术提供了一个大的关键空间,像素扩散以可接受的速度。安全性分析显示了对秘密密钥,普通医学图像和加密图像的任何微妙变化的加密和解密技术的高敏感依赖性。此外,所提出的技术具有足够大的关键空间来看脱离蛮力攻击。因此,所提出的技术是用于解决通信网络上医学图像的安全漏洞的潜在候选者。

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