V-Net architecture based advanced visually meaningful image encryption technique

被引:2
|
作者
Himthani, Varsha [1 ]
Dhaka, Vijaypal Singh [1 ]
Kaur, Manjit [2 ]
Hemrajani, Prashant [1 ]
机构
[1] Manipal Univ Jaipur, Dept Comp & Commun Engn, Jaipur 303007, Rajasthan, India
[2] Gwangju Inst Sci & Technol, Sch Elect Engn & Comp Sci, Gwangju 61005, South Korea
来源
JOURNAL OF DISCRETE MATHEMATICAL SCIENCES & CRYPTOGRAPHY | 2022年 / 25卷 / 07期
关键词
Visually meaningful image encryption; Image embedding; Information security; Steganography;
D O I
10.1080/09720529.2022.2133255
中图分类号
O29 [应用数学];
学科分类号
070104 ;
摘要
The visually meaningful image encryption (VMIE) technique is used to offer additional security to the noise-like encrypted image by implanting the secret image in the cover image. Generally, VMIE techniques follow two steps: pre-encryption and embedding. In this paper, an advanced V-Net architecture based VMIE technique is presented. V-Net architecture is based on a Convolution Neural Network (CNN) and offered medical image segmentation, that is utilized in the image into image steganography in the proposed work. In the proposed VMIE technique, the secret image is encrypted by utilizing the 5D chaotic map to provide high security, and the encrypted secret image is implanted into the cover image using a V-Net based embedding method. CNN-based image embedding methods offer high payload capacity and imperceptibility. In these methods, the encoder hides the secret image into the cover and the decoder reconstruct the secret image. Furthermore, a CNN-based efficient decoder is designed in the proposed method. Moreover, to validate the proposed method, standard evaluation parameters are analyzed.
引用
收藏
页码:2183 / 2194
页数:12
相关论文
empty
未找到相关数据