LVGG-IE:一种基于VGG的轻量级图像加密方案
Mingliang Sun1, Jie Yuan1, Xiaoyong Li1
1Key Laboratory of Trustworthy Distributed Computing and Service (BUPT), Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China.
Entropy (Basel, Switzerland)
|January 8, 2025
概括
本研究介绍了一种使用轻量级VGG网络 (LVGG-IE) 进行图像加密的新方法,以提高安全性. LVGG-IE计划确保图像加密的高安全性和效率,解决数字图像保护当前的挑战.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 密码学 密码学 密码学 密码学
背景情况:
- 图像安全日益受到人工智能和计算机科学进步的挑战.
- 现有的混乱和基于DNA的图像加密方法面临复杂性和退化问题.
- 图像加密中的深度学习集成正在芽,存在几个局限性.
研究的目的:
- 提出一种新,安全和高效的图像加密方案.
- 解决混乱系统中的安全退化和现有方法的复杂性.
- 利用深度学习来改善图像保护.
主要方法:
- 开发了一个轻量级VGG (LVGG) 网络,用于关键种子生成.
- 整合了密钥种子与一个混乱的系统,用于依赖于纯文本的密钥生成.
- 采用动态替换盒 (S-box) 和单连接 (SC) 层与VGG卷积用于图像编码和加密.
主要成果:
- 在相邻的像素之间实现了10-4的相关系数.
- 证明高的像素变化速率 (NPCR) 超过0.9958.
- 确认像素光圈变化的统一性 (UACI) 符合理论值.
结论:
- 拟议的LVGG-IE方案为图像加密提供了高安全性,效率和稳定性.
- 该方法有效地克服了现有的混乱和基于深度学习的方法的局限性.
- 该方案适用于需要安全图像保护的各种应用.
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