Image Steganography
18 papers with code • 0 benchmarks • 0 datasets
Image Steganography is the main content of information hiding. The sender conceal a secret message into a cover image, then get the container image called stego, and finish the secret message’s transmission on the public channel by transferring the stego image. Then the receiver part of the transmission can reveal the secret message out. Steganalysis is an attack to the steganography algorithm. The listener on the public channel intercept the image and analyze whether the image contains secret information.
Source: Invisible Steganography via Generative Adversarial Networks
Benchmarks
These leaderboards are used to track progress in Image Steganography
Latest papers with no code
A Novel Steganography Technique for Digital Images Using the Least Significant Bit Substitution Method
Embedding different sizes of a particular secret message in a different image (such as Gray, Texture, Aerial and RGB images) came out with about 5. 466 percent of better score.
Color Image steganography using Deep convolutional Autoencoders based on ResNet architecture
In the proposed method, all images are passed through the prepossess model which is a convolutional deep neural network with the aim of feature extraction.
FastStamp: Accelerating Neural Steganography and Digital Watermarking of Images on FPGAs
In this work, we design the first accelerator platform FastStamp to perform DNN based steganography and digital watermarking of images on hardware.
Image Generation Network for Covert Transmission in Online Social Network
Online social networks have stimulated communications over the Internet more than ever, making it possible for secret message transmission over such noisy channels.
Image Steganography based on Style Transfer
Image steganography is the art and science of using images as cover for covert communications.
Hiding Data in Colors: Secure and Lossless Deep Image Steganography via Conditional Invertible Neural Networks
Deep image steganography is a data hiding technology that conceal data in digital images via deep neural networks.
Robust Invertible Image Steganography
Previous image steganography methods are limited in hiding capacity and robustness, commonly vulnerable to distortion on container images such as Gaussian noise, Poisson noise, and lossy compression.
A Color Image Steganography Based on Frequency Sub-band Selection
Color image steganography based on deep learning is the art of hiding information in the color image.
Multitask Identity-Aware Image Steganography via Minimax Optimization
The key issue of the direct recognition is to preserve identity information of secret images into container images and make container images look similar to cover images at the same time.
Large-Capacity Image Steganography Based on Invertible Neural Networks
Many attempts have been made to hide information in images, where the main challenge is how to increase the payload capacity without the container image being detected as containing a message.
