Pinned Repositories
UCNet_Steganalysis
3D-steganography-based-on-FPD
An-Adaptable-Image-Steganography-Model-with-User-Customization
This paper, starting from actual user needs, proposes an adaptable image steganography model that can be customized by the user.
BBM
Non-Additive Cost Functions for JPEG Steganography Based on Block Boundary Maintenance
BET
Efficient JPEG Steganography Using Domain Transformation of Embedding Entropy. https://ieeexplore.ieee.org/document/8322237
CA-STC
The description of CA-STC
CC-JRM
Steganalysis of JPEG Images Using Rich Models. Copy from: http://dde.binghamton.edu/download/feature_extractors/
DCDT
DCTR
Low Complexity Features for JPEG Steganalysis Using Undecimated DCT. Copy form: http://dde.binghamton.edu/download/feature_extractors/
Deep-Steganalysis
PyTorch implementation of the classical image steganalysis networks, compatible with both grayscale and color images, and supporting multiple image sizes.
ych869's Repositories
ych869/PENet_Steganalysis
ych869/GAN-based-Symmetric-Embedding-Costs-Adjustment-for-Enhancing-Image-Steganographic-Security
ych869/GAIE
Efficient Audio Steganography using Generalized Audio Intrinsic Energy with Micro-Amplitude Modification Suppression
ych869/M_ISIC
Lattice-Aided Extraction of Spread-Spectrum Hidden Data
ych869/An-Adaptable-Image-Steganography-Model-with-User-Customization
This paper, starting from actual user needs, proposes an adaptable image steganography model that can be customized by the user.
ych869/Imperceptible-Medical-Image-Hiding-for-Secure-Healthcare
This paper proposes a medical image hiding method for secure healthcare.
ych869/CA-STC
The description of CA-STC
ych869/Deep-Steganalysis
PyTorch implementation of the classical image steganalysis networks, compatible with both grayscale and color images, and supporting multiple image sizes.
ych869/HEVC-MVPO-Video-steganalysis
ych869/3D-steganography-based-on-FPD
ych869/Polarized-Steganographic-Codes
Steganographic shcemes with polar codes and polarized steganographic channels.
ych869/UGS-TDSC
Source code for paper "Adversarial Steganography Embedding via Stego Generation and Selection"
ych869/MAE-TIFS
source code for paper "A New Adversarial Embedding Method for Enhancing Image Steganography"
ych869/UCNet_Steganalysis
ych869/Watermark-Vaccine
The code for ECCV2022 (Watermark Vaccine: Adversarial Attacks to Prevent Watermark Removal)
ych869/DCDT
ych869/h264_qdct_ptc
ych869/Feature-Extractors-for-Video-Steganalysis
To provide the stego community with C/C++ implementations of selected feature extractors mainly targeted at H.264 steganography.
ych869/PyTorch-GAN
PyTorch implementations of Generative Adversarial Networks.
ych869/Steganalytic-feature-extractor
SUPERB FEATURE EXTRACTOR
ych869/GMRF
Image Steganography with Symmetric Embedding using Gaussian Markov Random Field Model;Published in: IEEE Transactions on Circuits and Systems for Video Technology;https://ieeexplore.ieee.org/document/9112323
ych869/UERD
matlabcode: Using Statistical Image Model for JPEG Steganography: Uniform Embedding Revisited
ych869/GUED
A New Distortion Function Design for JPEG Steganography Using the Generalized Uniform Embedding Strategy
ych869/Pytorch-implementation-of-SRNet
A pytorch implementation of Deep Residual Network for Steganalysis of Digital Images (SRNet)
ych869/SiaStegNet
A Siamese CNN for Image Steganalysis
ych869/MiPOD
Content-Adaptive Steganography by Minimizing Statistical Detectability. Copy from: http://dde.binghamton.edu/download/stego_algorithms/
ych869/MVG
Multivariate Gaussian model for designing additive distortion for steganography. Copy from: http://dde.binghamton.edu/download/stego_algorithms/
ych869/WOW
Designing Steganographic Distortion Using Directional Filters. Copy from:http://dde.binghamton.edu/download/stego_algorithms/
ych869/Uniward
Universal Distortion Function for Steganography in an Arbitrary Domain. Copy from: http://dde.binghamton.edu/download/stego_algorithms/
ych869/STC-simulator
Minimizing Additive DistortionFunctions With Non-Binary Embedding Operation in Steganography. Copy form: http://dde.binghamton.edu/download/syndrome/