Log In Sign Up

Generating Steganographic Images via Adversarial Training

by   Jamie Hayes, et al.

Adversarial training was recently shown to be competitive against supervised learning methods on computer vision tasks, however, studies have mainly been confined to generative tasks such as image synthesis. In this paper, we apply adversarial training techniques to the discriminative task of learning a steganographic algorithm. Steganography is a collection of techniques for concealing information by embedding it within a non-secret medium, such as cover texts or images. We show that adversarial training can produce robust steganographic techniques: our unsupervised training scheme produces a steganographic algorithm that competes with state-of-the-art steganographic techniques, and produces a robust steganalyzer, which performs the discriminative task of deciding if an image contains secret information. We define a game between three parties, Alice, Bob and Eve, in order to simultaneously train both a steganographic algorithm and a steganalyzer. Alice and Bob attempt to communicate a secret message contained within an image, while Eve eavesdrops on their conversation and attempts to determine if secret information is embedded within the image. We represent Alice, Bob and Eve by neural networks, and validate our scheme on two independent image datasets, showing our novel method of studying steganographic problems is surprisingly competitive against established steganographic techniques.


page 5

page 7


Synchronization Detection and Recovery of Steganographic Messages with Adversarial Learning

As a means for secret communication, steganography aims at concealing a ...

Heard More Than Heard: An Audio Steganography Method Based on GAN

Audio steganography is a collection of techniques for concealing the exi...

The Enemy of My Enemy is My Friend: Exploring Inverse Adversaries for Improving Adversarial Training

Although current deep learning techniques have yielded superior performa...

Learning Symmetric and Asymmetric Steganography via Adversarial Training

Steganography refers to the art of concealing secret messages within mul...

Invisible Steganography via Generative Adversarial Network

Steganography and steganalysis are main content of information hiding, t...

Spatial Image Steganography Based on Generative Adversarial Network

With the recent development of deep learning on steganalysis, embedding ...

FaceSigns: Semi-Fragile Neural Watermarks for Media Authentication and Countering Deepfakes

Deepfakes and manipulated media are becoming a prominent threat due to t...

Code Repositories



view repo