SteganoGAN: High Capacity Image Steganography with GANs
원문 초록
Image steganography is a procedure for hiding messages inside pictures. While other techniques such as cryptography aim to prevent adversaries from reading the secret message, steganography aims to hide the presence of the message itself. In this paper, we propose a novel technique for hiding arbitrary binary data in images using generative adversarial networks which allow us to optimize the perceptual quality of the images produced by our model. We show that our approach achieves state-of-the-art payloads of 4.4 bits per pixel, evades detection by steganalysis tools, and is effective on images from multiple datasets. To enable fair comparisons, we have released an open source library that is available online at https://github.com/DAI-Lab/SteganoGAN.
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CLPSTNet: A Progressive Multi-Scale Convolutional Steganography Model Integrating Curriculum Learning
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Natias: Neuron Attribution based Transferable Image Adversarial Steganography
Cover-separable Fixed Neural Network Steganography via Deep Generative Models
DiffStega: Towards Universal Training-Free Coverless Image Steganography with Diffusion Models
Effective Message Hiding with Order-Preserving Mechanisms
토론
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