Steganographic Generative Adversarial Networks
Steganography is collection of methods to hide secret information ("payload") within non-secret information "container"). Its counterpart, Steganalysis, is the practice of determining if a message contains a hidden payload, and recovering it if possible. Presence of hidden payloads is typically detected by a binary classifier. In the present study, we propose a new model for generating image-like containers based on Deep Convolutional Generative Adversarial Networks (DCGAN). This approach allows to generate more setganalysis-secure message embedding using standard steganography algorithms. Experiment results demonstrate that the new model successfully deceives the steganography analyzer, and for this reason, can be used in steganographic applications.
Code (1)
Tasks
SteganalysisSimilar Papers 제목 키워드 기반
Generating Steganographic Images via Adversarial Training
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 pape…
Image GenerationDestruction of Image Steganography using Generative Adversarial Networks
Digital image steganalysis, or the detection of image steganography, has been studied in depth for years and is driven by Advanced Persistent Threat (APT) groups', such as APT37 Reaper, utilization of steganographic tech…
BlockingGenerative Adversarial NetworkImage SteganographySteganalysis+1Synchronized Detection and Recovery of Steganographic Messages with Adversarial Learning
In this work, we mainly study the mechanism of learning the steganographic algorithm as well as combining the learning process with adversarial learning to learn a good steganographic algorithm. To handle the problem of …
Learning Symmetric and Asymmetric Steganography via Adversarial Training
Steganography refers to the art of concealing secret messages within multiple media carriers so that an eavesdropper is unable to detect the presence and content of the hidden messages. In this paper, we firstly propose …
DecoderGraph-Stega: Semantic Controllable Steganographic Text Generation Guided by Knowledge Graph
Most of the existing text generative steganographic methods are based on coding the conditional probability distribution of each word during the generation process, and then selecting specific words according to the secr…
Text Generation