首页> 外文期刊>Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies >Analysis of zig-zag scan based modified feedback convolution algorithm against differential attacks and its application to image encryption
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Analysis of zig-zag scan based modified feedback convolution algorithm against differential attacks and its application to image encryption

机译:基于ZAG扫描的修改反馈卷积算法对差分攻击的分析及其在图像加密的应用

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摘要

In this paper, a novel zig-zag scan-based feedback convolution algorithm for image encryption against differential attacks is proposed. The two measures Number of Pixel Change Rate (NPCR) and Unified Average Changed Intensity (UACI) are commonly utilized for analyzing the differential attacks. From the study of the existing papers, even though high Number of Pixel Change Rate and Unified Average Changed Intensity values are obtained, a few values lie in the critical range of alpha-level significance which in turn increase the possibility of differential attacks. To overcome differential attacks, two aspects of scanning with different test cases are analyzed and from these analyses, it is concluded that zig-zag scan based feedback convolution in forward and reverse direction achieves good Number of Pixel Change Rate and Unified Average Changed Intensity without critical values. Zig-zag scan based feedback convolution in forward and reverse direction is enforced for key sequence generation and applied in diffusion process to achieve high level of security. Moreover, plain image related initial seed is also generated to overcome the chosen/known plain text attacks. Both numerical and theoretical analyses are performed to prove that the proposed encryption method is resistant to differential attacks. General security measures are carried out for the proposed method to validate its security level. From the simulations, it is shown that the proposed methodology has good keyspace, high key sensitivity, good randomness, and uniform distribution of cipher image pixels.
机译:本文提出了一种用于图像加密的基于新的Zig-ZAG扫描的反馈算法,用于针对差分攻击的图像加密。两个尺度像素变化率(NPCR)和统一平均改变强度(UACI)的数量通常用于分析差异攻击。从现有论文的研究来看,即使获得了大量的像素变化率和统一的平均改变强度值,少数值位于α级意义的临界范围内,这反过来增加了差异攻击的可能性。为了克服差异攻击,分析了使用不同测试用例的扫描的两个方面,并从这些分析中得出结论,前向和反向的基于Zig-Zag扫描的反馈卷积实现了良好数量的像素变化率,并且在没有关键的情况下实现良好的像素变化率和统一的平均改变强度价值观。基于ZAG扫描的前向和反向方向的反馈卷积被强制为关键序列生成并应用于扩散过程以实现高度的安全性。此外,还产生纯图像相关的初始种子以克服所选/已知的纯文本攻击。进行数值和理论分析来证明所提出的加密方法对差异攻击抵抗。概述验证其安全级别的方法进行一般安全措施。从模拟中,表明所提出的方法具有良好的keyspace,高键灵敏度,良好的随机性以及密码图像像素的均匀分布。

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