papers AI Learner
The Github is limit! Click to go to the new site.

SteganoGAN: Pushing the Limits of Image Steganography

2019-01-12
Kevin Alex Zhang, Alfredo Cuesta-Infante, Kalyan Veeramachaneni

Abstract

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 based on generative adversarial networks for hiding arbitrary binary data in images. 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.

Abstract (translated by Google)
URL

http://arxiv.org/abs/1901.03892

PDF

http://arxiv.org/pdf/1901.03892


Similar Posts

Comments