医学图像加密:改进的基于填充的GGH加密算法的应用

M. Sokouti, A. Zakerolhosseini, B. Sokouti
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引用次数: 22

摘要

医学图像是医学信息系统中重要而敏感的数据。为了在不安全的网络上传输医学图像,必须开发一种安全的加密算法。在安全服务的三个主要属性(即机密性、完整性和可用性)中,机密性是医生之间交换医学图像的最基本特征。Goldreich Goldwasser Halevi (GGH)算法是医学图像加密的一个很好的选择,因为该算法和敏感数据都是用数字矩阵表示的。此外,GGH算法不会增加图像的大小,因此其复杂度将保持在简单的O(n2)。然而,使用GGH算法的缺点之一是选择密文攻击。在我们的策略中,已经考虑到GGH算法的这个缺点,并通过在GGH加密过程之前应用填充(即蜗牛巡游XORing)来改进。为了评估它们的性能,考虑了三个测量标准,包括(i)像素变化率(NPCR), (ii)统一平均变化强度(UACI)和(iii)雪崩效应。在三种不同大小的图像上的结果表明,与标准GGH算法相比,填充GGH方法分别使UACI、NPCR和Avalanche的性能提高了近100%、35%和45%。此外,结果将使填充GGH抵抗密文、所选密文和统计攻击。此外,与所提出的方法在加密和解密过程方面增加的复杂性相比,将雪崩效应提高50%以上是一个有希望的成就。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Medical Image Encryption: An Application for Improved Padding Based GGH Encryption Algorithm
Medical images are regarded as important and sensitive data in the medical informatics systems. For transferring medical images over an insecure network, developing a secure encryption algorithm is necessary. Among the three main properties of security services (i.e., confidentiality, integrity, and availability), the confidentiality is the most essential feature for exchanging medical images among physicians. The Goldreich Goldwasser Halevi (GGH) algorithm can be a good choice for encrypting medical images as both the algorithm and sensitive data are represented by numeric matrices. Additionally, the GGH algorithm does not increase the size of the image and hence, its complexity will remain as simple as O(n2). However, one of the disadvantages of using the GGH algorithm is the Chosen Cipher Text attack. In our strategy, this shortcoming of GGH algorithm has been taken in to consideration and has been improved by applying the padding (i.e., snail tour XORing), before the GGH encryption process. For evaluating their performances, three measurement criteria are considered including (i) Number of Pixels Change Rate (NPCR), (ii) Unified Average Changing Intensity (UACI), and (iii) Avalanche effect. The results on three different sizes of images showed that padding GGH approach has improved UACI, NPCR, and Avalanche by almost 100%, 35%, and 45%, respectively, in comparison to the standard GGH algorithm. Also, the outcomes will make the padding GGH resist against the cipher text, the chosen cipher text, and the statistical attacks. Furthermore, increasing the avalanche effect of more than 50% is a promising achievement in comparison to the increased complexities of the proposed method in terms of encryption and decryption processes.
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