Image encryption algorithm based on multiple chaotic systems and improved Joseph block scrambling

Dingkang Mou, Yumin Dong
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Abstract

With the rapid development of digital information technology, images are increasingly used in various fields. To ensure the security of image data, prevent unauthorized tampering and leakage, maintain personal privacy, and protect intellectual property rights, this study proposes an innovative color image encryption algorithm. Initially, the Mersenne Twister algorithm is utilized to generate high-quality pseudo-random numbers, establishing a robust basis for subsequent operations. Subsequently, two distinct chaotic systems, the autonomous non-Hamiltonian chaotic system, and the Tent-Logistic-Cosine chaotic mapping, are employed to produce chaotic random sequences. These chaotic sequences are used to control the encoding and decoding process of the DNA, effectively scrambling the image pixels. Furthermore, the complexity of the encryption process is enhanced through improved Joseph block scrambling. After thorough experimental verification, research, and analysis, the average value of the information entropy test data reaches as high as 7.999. Additionally, the average value of the NPCR test data is 99.6101%, which closely approaches the ideal value of 99.6094%. This algorithm not only guarantees image quality but also substantially raises the difficulty level of decryption.
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基于多重混沌系统的图像加密算法和改进的约瑟夫块加扰算法
随着数字信息技术的飞速发展,图像越来越多地应用于各个领域。为了确保图像数据的安全,防止未经授权的篡改和泄漏,维护个人隐私,保护知识产权,本研究提出了一种创新的彩色图像加密算法。首先,利用梅森孪生算法生成高质量的伪随机数,为后续操作建立稳健的基础。随后,利用两个不同的混沌系统,即自主非哈密顿混沌系统和Tent-Logistic-Cosine混沌映射,产生混沌随机序列。这些混沌序列用于控制 DNA 的编码和解码过程,从而有效地扰乱图像像素。此外,通过改进约瑟夫块加扰技术,加密过程的复杂性也得到了提高。经过全面的实验验证、研究和分析,信息熵测试数据的平均值高达 7.999。此外,NPCR 测试数据的平均值为 99.6101%,接近 99.6094% 的理想值。该算法不仅保证了图像质量,还大大提高了解密难度。
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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