加密
计算机科学
理论计算机科学
概率加密
计算机工程
编码(集合论)
可扩展性
熵(时间箭头)
密文
密码分析
基于属性的加密
像素
磁盘加密硬件
密码学
算法
人工智能
混乱的
分布式计算
计算机视觉
洗牌
多重加密
密码
磁盘加密理论
图像(数学)
服务器
动态加密
计算机安全
赫农地图
链路加密
磁盘加密
嵌入式系统
有界函数
过程(计算)
作者
Yiting Lin,Yunlong Liao,Wenjun Zeng,Yunan Wei,Donglong Chen,Xiaochen Yuan,Yupeng Li,Uğur Erkan,Abdurrahim Toktaş,Chongfu Zhang,Yong Zhang,Suo Gao
标识
DOI:10.1109/tce.2026.3672135
摘要
The widespread adoption of consumer electronics (CE), particularly in smart home ecosystems, has led to the proliferation of intelligent devices such as smart cameras, video doorbells, and smart door locks. While these devices enhance convenience and automation, they generate massive amounts of visual data containing sensitive personal information, thereby increasing the risk of privacy leakage and challenging traditional encryption methods in consumer IoT networks. To address this issue, a cryptanalysis-driven image encryption scheme via a chaos-based 3D S-box and genetic code is proposed, specifically designed to safeguard visual privacy in consumer applications. First, a novel dynamical architecture, formally termed 3D Non-degenerate Hyperchaos (3D-NDHC), is constructed to serve as a robust entropy source. Explicitly defined as a globally bounded volume-expanding hyperchaotic system, 3D-NDHC distinguishes itself from traditional dissipative maps by exhibiting global robust hyperchaos and scalable complexity, where the Lyapunov exponents grow logarithmically with control parameters, ensuring high unpredictability. Next, a dynamically generated three-dimensional S-box driven by these chaotic sequences is introduced to perform efficient image permutation. Subsequently, a genetic code method enhanced by cryptanalysis is applied to confuse the permuted image matrix, specifically addressing the security vulnerabilities often inherent in lightweight encryption algorithms. Finally, under the control of pseudo-chaotic sequences, a lightweight wave diffusion process is employed to spread the pixel values and produce the final ciphertext image. In contrast to conventional algorithms that rely on standard encryption techniques, the proposed approach integrates a chaos-driven 3D S-box with a cryptanalysis-enhanced genetic code scheme. This combination introduces a high level of confusion and diffusion, significantly increasing the difficulty for attackers attempting to illegally decrypt sensitive images from smart devices. Experimental results and security analyses demonstrate that the scheme effectively resists various cryptographic attacks and outperforms several recently proposed image encryption algorithms, offering a robust solution for protecting digital image privacy in smart home environments.
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