加密
计算机科学
人工神经网络
图像(数学)
压缩(物理)
突变
方案(数学)
算法
遗传学
人工智能
材料科学
基因
计算机网络
数学
生物
复合材料
数学分析
作者
Yinghong Cao,Zhaocheng Liu,Kaihua Wang,Xiuguo Bi
出处
期刊:Physica Scripta
[IOP Publishing]
日期:2024-08-14
卷期号:99 (9): 095023-095023
被引量:3
标识
DOI:10.1088/1402-4896/ad6f79
摘要
Abstract In this paper, an efficient image compression encryption scheme is proposed. Firstly, compressing the image by using BP neural network before encryption, which not only saves the subsequent encryption and decryption time but also minimizes storage and transmission space. Secondly, Chialvo neuron model is used to generate chaotic sequences for the encryption process in the scheme, confusing the compressed image according to a confusion algorithm combining single-plane and cross-plane. Next, diffusing the confused image. Subsequently, the diffused image and chaotic sequences are DNA encoded, performing DNA same or operation (DNA mutual mutations) and DNA mutations (DNA self-mutations). Finally, the DNA mutations results are decoded to obtain the cipher image. Security tests and compression performance analysis show that the scheme can efficiently and securely compress and encrypt images of different sizes with higher reconstruction quality compared to other compression schemes.
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