DASM: Domain-Aware Sharpness Minimization for Multi-Domain Voice Stream Steganalysis

The growing use of information hiding in network streaming media for covert communication poses a significant security threat, necessitating the development of robust detection technologies. However, existing steganalysis methods for network voice streams mostly rely on data distributions in...

Stego Battlefield: Evaluating Image Steganography Attacks and Steganalysis Defenses

Image steganography is widely used to protect user privacy and enable covert communication. However, it can also be abused by the adversary as a covert channel to bypass content moderation, disseminate harmful semantics, and even hide malicious instructions in images to elicit dangerous outputs...

CVE-2026-34977

Aperi'Solve is an open-source steganalysis web platform. Prior to 3.2.1, when uploading a JPEG, a user can specify an optional password to accompany the JPEG. This password is then directly passed into an expect command, which is then subsequently passed into a bash -c command, without any form o...

On the Possible Detectability of Image-In-Image Steganography

This paper investigates the detectability of popular imagein-image steganography schemes 1, 2, 3, 4, 5. In this paradigm, the payload is usually an image of the same size as the Cover image, leading to very high embedding rates. We first show that the embedding yields a mixing process that is...

H.265/HEVC Video Steganalysis Based on CU Block Structure Gradients and IPM Mapping

Existing H.265/HEVC video steganalysis research mainly focuses on statistical feature modeling at the levels of motion vectors MV, intra prediction modes IPM, or transform coefficients. In contrast, studies targeting the coding-structure level - especially the analysis of block-level steganograph...

Rethinking Security of Diffusion-Based Generative Steganography

Generative image steganography is a technique that conceals secret messages within generated images, without relying on pre-existing cover images. Recently, a number of diffusion model-based generative image steganography DM-GIS methods have been introduced, which effectively combat traditional...

Defining Cost Function of Steganography with Large Language Models

In this paper, we make the first attempt towards defining cost function of steganography with large language models LLMs, which is totally different from previous works that rely heavily on expert knowledge or require large-scale datasets for cost learning. To achieve this goal, a two-stage...

Systematically Deconstructing APVD Steganography and Its Payload with a Unified Deep Learning Paradigm

In the era of digital communication, steganography allows covert embedding of data within media files. Adaptive Pixel Value Differencing APVD is a steganographic method valued for its high embedding capacity and invisibility, posing challenges for traditional steganalysis. This paper proposes a...

Exploring AI in Steganography and Steganalysis: Trends, Clusters, and Sustainable Development Potential

Steganography and steganalysis are strongly related subjects of information security. Over the past decade, many powerful and efficient artificial intelligence AI - driven techniques have been designed and presented during research into steganography as well as steganalysis. This study presents a...

Targeted Pooled Latent-Space Steganalysis Applied to Generative Steganography, with a Fix

Steganographic schemes dedicated to generated images modify the seed vector in the latent space to embed a message, whereas most steganalysis methods attempt to detect the embedding in the image space. This paper proposes to perform steganalysis in the latent space by modeling the statistical...

Enhanced Deep Learning DeepFake Detection Integrating Handcrafted Features

The rapid advancement of deepfake and face swap technologies has raised significant concerns in digital security, particularly in identity verification and onboarding processes. Conventional detection methods often struggle to generalize against sophisticated facial manipulations. This study...

GSDFuse: Capturing Cognitive Inconsistencies from Multi-Dimensional Weak Signals in Social Media Steganalysis

The ubiquity of social media platforms facilitates malicious linguistic steganography, posing significant security risks. Steganalysis is profoundly hindered by the challenge of identifying subtle cognitive inconsistencies arising from textual fragmentation and complex dialogue structures, and th...

GIFDL: Generated Image Fluctuation Distortion Learning for Enhancing Steganographic Security

Minimum distortion steganography is currently the mainstream method for modification-based steganography. A key issue in this method is how to define steganographic distortion. With the rapid development of deep learning technology, the definition of distortion has evolved from manual design to...

Machine Learning Image Steganalysis: Aletheia

Aletheia is a steganalysis tool for the detection of hidden messages in images. The goal of steganalysis is to identify suspected packages, determine whether or not they have a payload encoded into them, and, if possible, recover that payload. Unlike cryptanalysis, steganalysis generally starts...

Steganography in contemporary cyberattacks

Steganography is the practice of sending data in a concealed format so the very fact of sending the data is disguised. The word steganography is a combination of the Greek words στεγανός steganos, meaning "covered, concealed, or protected", and γράφειν graphein meaning "writing". Unlike...

[Stegano 0.4] Python Steganography Module

Stéganô is a Python Steganography module. Steganography is the art and science of writing hidden messages in such a way that no one, apart from the sender and intended recipient, suspects the existence of the message, a form of security through obscurity. Consequently, functions provided by Stéga...