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GAN-Based Steganography with the Concatenation of Multiple Feature Maps

https://doi.org/10.1007/978-3-030-43575-2_1
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/sec.1094openalex-snapshot
Digital image steganalysis based on local textural features and double dimensionality reduction
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-snapshot
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-77380-3_51openalex-snapshot
SSGAN: Secure Steganography Based on Generative Adversarial Networks
inferredcites →https://doi.org/10.1007/978-3-642-16435-4_13openalex-snapshot
Using High-Dimensional Image Models to Perform Highly Undetectable Steganography
inferredcites →https://doi.org/10.1109/access.2018.2841415openalex-snapshot
Robust Batch Steganography in Social Networks With Non-Uniform Payload and Data Decomposition
inferredcites →https://doi.org/10.1109/lsp.2006.870357openalex-snapshot
LSB matching revisited
inferredcites →https://doi.org/10.1109/lsp.2016.2548421openalex-snapshot
Structural Design of Convolutional Neural Networks for Steganalysis
inferredcites →https://doi.org/10.1109/lsp.2017.2745572openalex-snapshot
Automatic Steganographic Distortion Learning Using a Generative Adversarial Network
inferredcites →https://doi.org/10.1109/tifs.2011.2134094openalex-snapshot
Minimizing Additive Distortion in Steganography Using Syndrome-Trellis Codes
inferredcites →https://doi.org/10.1109/tifs.2012.2190402openalex-snapshot
Rich Models for Steganalysis of Digital Images
inferredcites →https://doi.org/10.1109/tifs.2014.2326954openalex-snapshot
Investigation on Cost Assignment in Spatial Image Steganography
inferredcites →https://doi.org/10.1109/tifs.2015.2486744openalex-snapshot
Content-Adaptive Steganography by Minimizing Statistical Detectability
inferredcites →https://doi.org/10.1109/tifs.2015.2496910openalex-snapshot
Steganalysis Over Large-Scale Social Networks With High-Order Joint Features and Clustering Ensembles
inferredcites →https://doi.org/10.1109/tifs.2017.2710946openalex-snapshot
Deep Learning Hierarchical Representations for Image Steganalysis
inferredcites →https://doi.org/10.1109/wifs.2012.6412655openalex-snapshot
Designing steganographic distortion using directional filters
inferredcites →https://doi.org/10.1117/12.2083479openalex-snapshot
Deep learning for steganalysis via convolutional neural networks
inferredcites →https://doi.org/10.1117/12.2559429openalex-snapshot
Steganographic generative adversarial networks
inferredcites →https://doi.org/10.1145/3206004.3206012openalex-snapshot
Adversarial Examples Against Deep Neural Network based Steganalysis
inferredcites →https://doi.org/10.1186/1687-417x-2014-1openalex-snapshot
Universal distortion function for steganography in an arbitrary domain
inferredcites →https://doi.org/10.48550/arxiv.1804.07939openalex-snapshot
Spatial Image Steganography Based on Generative Adversarial Network

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4533667openalex-extracted
MedSteGAN: Medical Embedding-Optimized Steganography with Improved GAN
inferred← citeshttps://doi.org/10.1007/s10515-025-00569-7openalex-snapshot
MalModel: hiding malicious payload in mobile deep learning models with black-box backdoor attack
inferred← citeshttps://doi.org/10.1007/s42044-026-00413-5openalex-snapshot
A systematic literature review on Generative Adversarial Networks (GANs) based audio steganography
inferred← citeshttps://doi.org/10.1016/j.sigpro.2021.108341openalex-snapshot
GAN-based spatial image steganography with cross feedback mechanism
inferred← citeshttps://doi.org/10.1016/j.sigpro.2024.109546openalex-snapshot
Medical steganography: Enhanced security and image quality, and new S-Q assessment
inferred← citeshttps://doi.org/10.1109/ipec61310.2024.00054openalex-snapshot
Robust Image Steganography Model Based on Discrete-Dual-Tree Complex Wavelet Transform and Invertible Neural Network
inferred← citeshttps://doi.org/10.1109/lsp.2022.3152897openalex-snapshot
Ensemble Stego Selection for Enhancing Image Steganography
inferred← citeshttps://doi.org/10.1109/tcsvt.2025.3602508openalex-snapshot
Fearless of Noise: Robust Image-in-Image Hiding Using Dual-Tree Complex Wavelet Transform and State Space Model
inferred← citeshttps://doi.org/10.1109/tmm.2023.3307970openalex-snapshot
iSCMIS:Spatial-Channel Attention Based Deep Invertible Network for Multi-Image Steganography
inferred← citeshttps://doi.org/10.1109/tmm.2024.3353543openalex-snapshot
ARES: On Adversarial Robustness Enhancement for Image Steganographic Cost Learning
inferred← citeshttps://doi.org/10.1109/tnse.2021.3137829openalex-snapshot
High-Capacity Steganography Using Object Addition-Based Cover Enhancement for Secure Communication in Networks
inferred← citeshttps://doi.org/10.3233/faia230489openalex-snapshot
SUDS: Sanitizing Universal and Dependent Steganography
inferred← citeshttps://doi.org/10.36227/techrxiv.16755457openalex-snapshot
Stegomalware: A Systematic Survey of Malware Hiding and Detection in Images, Machine Learning Models and Research Challenges
inferred← citeshttps://doi.org/10.36227/techrxiv.16755457.v1openalex-snapshot
Stegomalware: A Systematic Survey of Malware Hiding and Detection in Images, Machine Learning Models and Research Challenges
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