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一个基于Hyperchaos和Hopfield混沌神经网络的新型彩色图像加密方案
Yanan Wu1, Jian Zeng1, Wenjie Dong2
1Electronic Engineering College, Heilongjiang University, Harbin 150080, China.
Entropy (Basel, Switzerland)
|July 8, 2023
概括
本研究介绍了一种新的与纯文本相关的彩色图像加密方案,使用五维超混沌系统和霍普菲尔德混乱神经网络. 该方法增强了钥匙空间和对攻击的安全性,为保护敏感信息提供了强大的解决方案.
科学领域:
- 密码学 密码学 密码学 密码学
- 图像处理 图像处理
- 应用数学 应用数学 应用数学
背景情况:
- 现有的加密方案存在关键空间有限,缺少一次性,结构简单,危及敏感数据的安全性.
- 在数字时代,为数字图像开发安全和强大的加密方法至关重要.
研究的目的:
- 提出一种与纯文本相关的彩色图像加密方案,以解决现有方法的局限性.
- 为了提高图像加密算法的安全性和密钥空间.
- 通过先进的加密技术,确保敏感信息保持安全.
主要方法:
- 一个新的五维超混沌系统的构建和性能分析.
- 将超混沌系统与霍普菲尔德混沌神经网络集成为新的加密算法.
- 通过图像块化生成与纯文本相关的密钥.
- 使用来自系统的伪随机序列来进行关键流.
- 实现像素级混和DNA操作用于扩散加密,基于混乱序列的动态规则选择.
主要成果:
- 与现有方法相比,拟议的方案显著改善了关键空间.
- 加密算法证明了对各种攻击的抵抗力.
- 该方法实现了对加密图像的令人满意的视觉隐藏结果.
- 构建的超混沌系统和霍普菲尔德混沌神经网络有效地产生强大的关键流.
结论:
- 开发的加密方案提供了增强的安全性和更大的密钥空间,克服了先前方法的局限性.
- 超混沌系统和混乱神经网络的集成为安全的图像加密提供了一个强大的工具.
- 拟议的算法是保护彩色图像中的敏感信息的有希望的解决方案.
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