基于ANN的混沌PRNG在新奇的动混沌系统中及其通过二维希尔伯特曲线对图像加密的应用
Aceng Sambas1,2, Xuncai Zhang3, Issam A R Moghrabi4,5
1Faculty of Informatics and Computing, Universiti Sultan Zainal Abidin, Kampung Gong Badak, 21300, Kuala Terengganu, Malaysia.
Scientific reports
|November 28, 2024
概括
研究人员开发了一种具有对称吸引器的新奇混沌 (NJC) 振荡器. 这个系统通过传统的动态和神经网络进行分析,构成了基于混乱的强大的图像加密算法的基础.
科学领域:
- 非线性动力学是一种非线性动力学.
- 混沌理论 混沌理论
- 安全的通信安全的通信.
背景情况:
- 混乱系统提供了复杂的动态,适合密码学.
- 具有对称吸引器的新型Jerk Chaotic (NJC) 振荡器具有独特的动态特性.
- 对平衡点的分析对于理解系统稳定性至关重要.
研究的目的:
- 介绍和分析一个新型类型的对称的新混沌 (NJC) 振荡器.
- 调查拟议的NJC系统的动态行为.
- 使用NJC系统开发和验证基于混乱的图像加密算法.
主要方法:
- 两叉图,相位肖像和莱普诺夫指数用于动态分析.
- 多系统用于电子实现和验证.
- 送前传神经网络 (FFNN) 建模用于系统近似.
- 使用Dormand Prince算法的数值解决方案.
- 基于混沌的图像加密使用DNA编码和希尔伯特曲线.
主要成果:
- 拟议的NJC系统表现出三个不稳定的-焦点平衡点.
- 理论分析通过Multisim模拟和数值解决方案来证实.
- 开发了一个有效的FFNN模型用于Jerk混沌系统.
- 基于混乱的图像加密算法表现出强大的抗各种攻击的弹性.
结论:
- 新的NJC振荡器具有有趣的动态特性.
- 开发的图像加密算法强大而安全.
- 混沌系统与神经网络和先进加密技术的整合显示出显著的前景.
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