Results 41 to 50 of about 6,150 (193)

Spatial Steganalysis Based on Non-Local Block and Multi-Channel Convolutional Networks

IEEE Access, 2022
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

Towards Steganography Detection Through Network Traffic Visualisation

, 2012
The paper presents initial step toward new network anomaly detection method that is based on traffic visualisation. The key design principle of the proposed approach is the lack of direct, linear time dependencies for the created network traffic ...
Jankowski, Bartosz, Mazurczyk, Wojciech, Szczypiorski, Krzysztof   +2 more
core   +1 more source

Frame-Wise Steganalysis Based on Mask-Gating Attention and Deep Residual Bilinear Interaction Mechanisms for Low-Bit-Rate Speech Streams

Journal of Cybersecurity and Privacy
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, Azizol Abdullah, Normalia Samian, Nuur Alifah Roslan   +3 more
doaj   +1 more source

Deep Convolutional Neural Network to Detect J-UNIWARD

, 2017
This paper presents an empirical study on applying convolutional neural networks (CNNs) to detecting J-UNIWARD, one of the most secure JPEG steganographic method.
Ioffe Sergey, Nair Vinod, Qian Yinlong, Sedighi Vahid   +3 more
core   +1 more source

A comprehensive review of video steganalysis

IET Image Processing, 2022
Steganography is the art of secret communication and steganalysis is the art of detecting the hidden messages embedded in digital media covers. One of the covers that is gaining interest in the field is video. Presently, the global IP video traffic forms
Mourad Bouzegza, Ammar Belatreche, Ahmed Bouridane, Mohamed Tounsi   +3 more
doaj   +1 more source

Convolutional Neural Network Steganalysis's Application to Steganography

, 2017
This paper presents a novel approach to increase the performance bounds of image steganography under the criteria of minimizing distortion. The proposed approach utilizes a steganalysis convolutional neural network (CNN) framework to understand an image ...
Agarwal, Chirag, Aloraini, Mohammed, Schonfeld, Dan, Sharifzadeh, Mehdi   +3 more
core   +1 more source

Steganalysis of AMR Speech Based on Multiple Classifiers Combination

IEEE Access, 2019
In this paper, we focus on steganalysis in adaptive multi-rate (AMR) speech streams, whose goal is to detect covert communication behaviors effectively to prevent illegal uses of AMR steganography.
Hui Tian, Jie Liu, Chin-Chen Chang, Chih-Cheng Chen, Yongfeng Huang   +4 more
doaj   +1 more source

Recasting Residual-based Local Descriptors as Convolutional Neural Networks: an Application to Image Forgery Detection

, 2017
Local descriptors based on the image noise residual have proven extremely effective for a number of forensic applications, like forgery detection and localization.
Cozzolino, Davide, Poggi, Giovanni, Verdoliva, Luisa   +2 more
core   +1 more source

DrLS: Distortion‐Resistant Lossless Steganography via Colour Depth Interpolation

CAAI Transactions on Intelligence Technology, EarlyView.
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, Xuanyu Zhang, Xiandong Meng, Jian Zhang   +3 more
wiley   +1 more source

SNENet: An adaptive stego noise extraction network using parallel dilated convolution for JPEG image steganalysis

IET Image Processing, 2023
The steganalysis for JPEG image is an important research topic, as the enormous popularity of JPEG image on Internet. However, the stego noise feature extraction process of the existing deep learning‐based steganalytic methods are not adaptive enough to ...
Wentong Fan, Zhenyu Li, Hao Li, Yi Zhang, Xiangyang Luo   +4 more
doaj   +1 more source