Radix Trie improved Nahrain chaotic map-based image encryption model for effective image encryption process

Fazly Salleh Abas , R Arulmurugan
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引用次数: 2

Abstract

As the intrinsic features of images include huge size and additional correlation prevailing among pixels, it is tedious to accomplish by using outdated models. The cryptographic features of Chaotic Maps (CM), including early criteria and random nature, aid in designing novel Image Encryption (IE) methods. In this paper, Nahrain Map with Radix Trie-based Image Encryption (NMRTIE) model is proposed to guarantee image encryption that resists known attacks that could be launched during its transmission in the cloud environment. The propounded NMRTIE model includes three essential phases: NCM-based Image Encryption (IE), Radix Trie (RT) based scrambling, and incessant diffusion. Initially, the NCM model uses more than one chaotic function to produce a sequence of keys. The RT model eases scrambling, where the rows and columns' pixels are swapped substantially. Lastly, the propounded diffusion scheme cooperates with NCM to produce key streams for remarkably hastening diffusion and dispersing effect. The propounded NMRTIE model is evaluated, and the results are confirmed based on numerous characteristics. The investigational consequence confirms that the propounded NMRTIE scheme is more appropriate than the associated approaches.

改进了基于Nahrain混沌映射的图像加密模型,实现了有效的图像加密过程
由于图像的固有特征包括巨大的尺寸和像素之间普遍存在的额外相关性,使用过时的模型来完成是繁琐的。混沌映射(CM)的密码学特征,包括早期准则和随机性,有助于设计新的图像加密(IE)方法。为了保证图像加密能够抵抗在云环境中传输过程中可能受到的已知攻击,本文提出了带有基于基数trie的图像加密(NMRTIE)模型的Nahrain Map。提出的NMRTIE模型包括三个基本阶段:基于ncm的图像加密(IE),基于基数Trie (RT)的置乱和不间断扩散。最初,NCM模型使用多个混沌函数来产生一个键序列。RT模型简化了置乱,其中行和列的像素被大量交换。最后,提出的扩散方案与NCM相结合,产生了显著加速扩散和分散效果的关键流。对提出的NMRTIE模型进行了评估,并根据许多特征对结果进行了验证。研究结果证实,所提出的NMRTIE方案比相关方法更合适。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
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