灵活的视觉安全图像加密与元学习压缩和混乱系统.
Wei Chen1, Yichuan Wang2, Cheng Shi1
1School of Computer Science and Engineering, Xi'an University of Technology, Xi'an 710048, China.
概括
本研究介绍了一种使用元学习和混乱系统的新型图像加密方案,以确保安全,高质量的视觉数据. 这种灵活的方法在广泛的应用中平衡了运行时间和图像质量.
科学领域:
- 计算机科学 计算机科学
- 信息安全 信息安全
- 人工智能的人工智能
背景情况:
- 越来越多的人在各种应用中对安全的数字图像加密的需求.
- 现有方法的局限性包括安全性不足和解密图像质量差.
- 需要先进的技术,整合视觉数据的压缩和加密.
研究的目的:
- 提出一个灵活而安全的图像加密方案.
- 为了提高解密的图像质量和加密安全性.
- 为图像安全利用元学习,混乱系统和深度学习.
主要方法:
- 开发了一个超学习压缩重建网络,具有动态辅助输入,用于高质量的图像压缩.
- 通过将2D-IS混乱系统与图像加密的深度学习网络相结合,构建了一个新的IS-DP混乱系统.
- 实现了无损LSB-2^k校正嵌入方法,将秘密图像嵌入到载体图像中.
主要成果:
- 实现了高质量的压缩和数字图像的视觉安全加密.
- 证明了拟议的IS-DP混乱系统和元学习方法的有效性.
- 验证了深度学习方法在集成加密和压缩任务中的可行性.
结论:
- 拟议的方案提供了一个灵活的解决方案,用于视觉安全的图像加密.
- 超级学习提供了适应性,允许用户平衡性能和质量.
- 深度学习和混乱系统的集成显示了高级图像安全应用的巨大潜力.
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