A New High Capacity Image Steganography Method Combined With Image Elliptic Curve Cryptography and Deep Neural Network

Image steganography is a technology that hides sensitive information into an image. The traditional image steganography method tends to securely embed secret information in the host image so that the payload capacity is almost ignored and the steganographic image quality needs to be improved for the...

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Bibliographic Details
Published in:IEEE access 2020, Vol.8, p.25777-25788
Main Authors: Duan, Xintao, Guo, Daidou, Liu, Nao, Li, Baoxia, Gou, Mengxiao, Qin, Chuan
Format: Article
Language:English
Subjects:
Artificial neural networks
Cryptography
Curves
DCT
Decoding
Deep learning
deep neural network
Discrete cosine transform
Discrete cosine transforms
ECC
Elliptic curve cryptography
Image quality
Image steganography
Machine learning
Neural networks
SegNet
Signal to noise ratio
Steganography
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Summary:Image steganography is a technology that hides sensitive information into an image. The traditional image steganography method tends to securely embed secret information in the host image so that the payload capacity is almost ignored and the steganographic image quality needs to be improved for the Human Visual System(HVS). Therefore, in this work, we propose a new high capacity image steganography method based on deep learning. The Discrete Cosine Transform(DCT) is used to transform the secret image, and then the transformed image is encrypted by Elliptic Curve Cryptography(ECC) to improve the anti-detection property of the obtained image. To improve steganographic capacity, the SegNet Deep Neural Network with a set of Hiding and Extraction networks enables steganography and extraction of full-size images. The experimental results show that the method can effectively allocate each pixel in the image so that the relative capacity of steganography reaches 1. Besides, the image obtained using this steganography method has higher Peak Signal-to-Noise Ratio(PSNR) and Structural Similarity Index(SSIM) values, reaching 40dB and 0.96, respectively.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2020.2971528