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Steganalysis

Detect the usage of Steganography

Papers

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Showing 51–75 of 96 papers

TitleStatusHype
Semantic-Preserving Linguistic Steganography by Pivot Translation and Semantic-Aware Bins Coding—0
SSGAN: Secure Steganography Based on Generative Adversarial Networks—0
State-of-the-art Advances of Deep-learning Linguistic Steganalysis Research—0
Steganalysis of Image with Adaptively Parametric Activation—0
Steganalysis on Digital Watermarking: Is Your Defense Truly Impervious?—0
StegColNet: Steganalysis based on an ensemble colorspace approach—0
Structural Design of Convolutional Neural Networks for Steganalysis—0
Towards Imperceptible JPEG Image Hiding: Multi-range Representations-driven Adversarial Stego Generation—0
TSCL:Multi-party loss Balancing scheme for deep learning Image steganography based on Curriculum learning—0
Universal Deep Network for Steganalysis of Color Image based on Channel Representation—0
Unsupervised Steganalysis Based on Artificial Training Sets—0
UP4LS: User Profile Constructed by Multiple Attributes for Enhancing Linguistic Steganalysis—0
Using contrastive learning to improve the performance of steganalysis schemes—0
Image Generation Network for Covert Transmission in Online Social Network—0
Shackled Dancing: A Bit-Locked Diffusion Algorithm for Lossless and Controllable Image Steganography—0
Adversarial Embedding: A robust and elusive Steganography and Watermarking technique—0
A Novel Approach to Image Steganography Using Generative Adversarial Networks—0
A One-dimensional HEVC video steganalysis method using the Optimality of Predicted Motion Vectors—0
A Siamese CNN for Image Steganalysis—0
Blind Data Adaptation to tackle Covariate Shift in Operational Steganalysis—0
CNN-Assisted Steganography -- Integrating Machine Learning with Established Steganographic Techniques—0
Content Bias in Deep Learning Image Age Approximation: A new Approach Towards better Explainability—0
Continual Learning for Steganalysis—0
Coverless information hiding based on Generative Model—0
Decamouflage: A Framework to Detect Image-Scaling Attacks on Convolutional Neural Networks—0
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