Results 41 to 50 of about 6,282 (220)
The increasing digitization offers new ways, possibilities and needs for a secure transmission of information. Steganography and its analysis constitute an essential part of IT-Security. In this work we show how methods of blind-steganalysis can be improved to work in non-blind scenarios.
Niklas Bunzel +2 more
openaire +3 more sources
Spatial Steganalysis Based on Non-Local Block and Multi-Channel Convolutional Networks
Image steganalysis aims to detect whether secret information is hidden in images and is a means to solve the communication security. Recently, a series of convolutional neural network-based steganalysis models has been proposed and has achieved ...
Xu Han, Tao Zhang
doaj +1 more source
GBRAS-Net: A Convolutional Neural Network Architecture for Spatial Image Steganalysis
Advances in Deep Learning (DL) have provided alternative approaches to various complex problems, including the domain of spatial image steganalysis using Convolutional Neural Networks (CNN).
Tabares-Soto Reinel +9 more
semanticscholar +1 more source
Steganography is conducive to communication security, but the abuse of steganography brings many potential dangers. And then, steganalysis plays an important role in preventing the abuse of steganography.
Zhujun Jin +3 more
doaj +1 more source
Frame-wise steganalysis is a crucial task in low-bit-rate speech streams that can achieve active defense. However, there is no common theory on how to extract steganalysis features for frame-wise steganalysis.
Congcong Sun +3 more
doaj +1 more source
A Novel Image Steganography Method via Deep Convolutional Generative Adversarial Networks
The security of image steganography is an important basis for evaluating steganography algorithms. Steganography has recently made great progress in the long-term confrontation with steganalysis.
Donghui Hu +4 more
doaj +1 more source
Preprocessing Enhancement Method for Spatial Domain Steganalysis
In the field of steganalysis, in recent years, the research focus has mostly been on optimizing the structures of neural networks, while the application of high-pass filters is still limited to the simple selection of filters and simple adjustment of the
Xueming Duan +3 more
doaj +1 more source
Image Steganalysis of Low Embedding Rate Based on the Attention Mechanism and Transfer Learning
In recent years, some research results have been achieved in the field of image steganalysis. However, there are still problems of difficulty in extracting steganographic features from images with low embedding rates and unsatisfactory detection ...
Shouyue Liu +5 more
semanticscholar +1 more source
Progressive Randomization for Steganalysis [PDF]
In this paper, we describe a new methodology to detect the presence of hidden digital content in the Least Significant Bits (LSB) of images. We introduce the Progressive Randomization (PR) technique that captures statistical artifacts inserted during the hiding process.
Anderson Rocha 0001, Siome Goldenstein
openaire +1 more source
DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation
ABSTRACT The lossless data steganography is to hide a certain amount of information into a container image. Previous lossless steganography methods fail to strike a balance between capacity, imperceptibility, accuracy, and robustness, commonly vulnerable to distortion on container images.
Youmin Xu +3 more
wiley +1 more source

