An effective encryption approach using a combination of a non-chain ring and a four-dimensional chaotic map.

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES Cognitive Neurodynamics Pub Date : 2025-12-01 Epub Date: 2025-01-15 DOI:10.1007/s11571-025-10217-1
Muhammad Umair Safdar, Tariq Shah, Asif Ali
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Abstract

Algebraic structures are highly effective in designing symmetric key cryptosystems; however, if the key space is not sufficiently large, such systems become vulnerable to brute-force attacks. To address this challenge, our research focuses on enlarging the key space in symmetric key schemes by integrating the non-chain ring with a four-dimensional chaotic system. While chaotic maps offer significant potential for data processing, relying solely on them does not fully leverage their operational advantages. Therefore, it is essential to incorporate algebraic structures that enhance the complexity of the scheme. In the proposed technique, four-dimensional chaotic sequences are employed for image pixel permutation, diffusion, and exclusive-or operations. The scheme is further strengthened against chosen and known plaintext attacks by incorporating pixel values during the exclusive-or operation, where images are XORed with hashed images and keys generated from chaotic sequences. The effectiveness of the technique, its resilience to various forms of attack, and its feasibility for practical implementation are demonstrated through extensive testing and a comprehensive security analysis.

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一种利用非链环和四维混沌映射相结合的有效加密方法。
代数结构是设计对称密钥密码系统的有效方法。但是,如果密钥空间不够大,这样的系统就容易受到暴力攻击。为了解决这一挑战,我们的研究重点是通过将非链环与四维混沌系统集成来扩大对称密钥方案中的密钥空间。虽然混沌地图为数据处理提供了巨大的潜力,但仅仅依赖于它们并不能充分利用它们的操作优势。因此,有必要纳入代数结构,以提高方案的复杂性。在该技术中,采用四维混沌序列进行图像像素排列、扩散和异或运算。通过在异或操作期间合并像素值,该方案进一步加强了针对选择和已知明文攻击的能力,其中图像与从混沌序列生成的散列图像和密钥进行xor。通过广泛的测试和全面的安全分析,证明了该技术的有效性,其对各种形式攻击的弹性以及实际实施的可行性。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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