基于泄漏和时变延迟的神经网络的各种图像密码分析

IF 1.4 4区工程技术 Q2 ENGINEERING, MULTIDISCIPLINARY

International Journal of Nonlinear Sciences and Numerical Simulation Pub Date : 2022-10-11 DOI:10.1515/ijnsns-2021-0444

M. Manikandan, S. Ong

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引用次数: 0

摘要

本文的主要目的是为每个人提供一种有效的图像加密，以便在将自己的记录保存在社交网络中时保护自己的记录。我们用合适的密钥作为延迟模糊细胞神经网络(fcnn)的参数值，构造了延迟模糊细胞神经网络(fcnn)，得到了对图像进行加密的不规则动态信号(解)。我们总共使用了42个参数作为关键灵敏度，其量级为10−15，其中初始条件参数的三个元素的灵敏度为10−14。最后，与已有文献进行了对比。实验结果表明，该算法是一种新颖的图像加密整体解决方案。

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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Cryptanalysis of various images based on neural networks with leakage and time varying delays

Abstract The main objective of this paper is to provide an efficient image encryption for each and every single person in order to secure their own records while saving them in social networks. We have formulated the delayed fuzzy cellular neural networks (FCNNs) with suitable keys that are the values of the parameters of FCNNs and obtain the irregular dynamical signal (solution) which encrypts the images. We have utilized entirely 42 parameters as a key sensitivity in the order of 10−15 among them three elements of initial condition parameters are sensitive to the order of 10−14. Lastly, comparison results are provided with the existing literature. The measurements show that the proposed algorithm is a novel overall solution for image encryption.

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来源期刊

International Journal of Nonlinear Sciences and Numerical Simulation 工程技术-工程：综合

CiteScore

2.80

自引率

6.70%

发文量

117

审稿时长

13.7 months

期刊介绍： The International Journal of Nonlinear Sciences and Numerical Simulation publishes original papers on all subjects relevant to nonlinear sciences and numerical simulation. The journal is directed at Researchers in Nonlinear Sciences, Engineers, and Computational Scientists, Economists, and others, who either study the nature of nonlinear problems or conduct numerical simulations of nonlinear problems.