Digital image steganalysis based on local textural features and double dimensionality reduction-Reference-Cited by-同舟云学术

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Digital image steganalysis based on local textural features and double dimensionality reduction

Published:2014-10-14 Issue:8 Volume:9 Page:729-736
ISSN:1939-0114
Container-title:Security and Communication Networks
language:en
Short-container-title:Security Comm. Networks

Author:

Li Fengyong¹,Zhang Xinpeng²,Cheng Hang²³,Yu Jiang²

Affiliation:

1. College of Computer Science and Technology; Shanghai University of Electric Power; Shanghai 200090 China

2. School of Communication and Information Engineering; Shanghai University; Shanghai 200444 China

3. College of Mathematics and Computer Science; Fuzhou University; Fuzhou 350108 China

Publisher

Wiley

Subject

Computer Networks and Communications,Information Systems

Reference17 articles.

1. Edge adaptive image steganography based on LSB matching revisited;Luo;IEEE Transactions on Information Forensics and Security,2010

2. Using high-dimensional image models to perform highly undetectable steganography;Pevny;Proceedings 12th International Workshop on Information Hiding,2010

3. Holub V Fridrich J Designing steganographic distortion using directional filters Proceedings 4th IEEE International Workshop on Information Forensics and Security Tenerife, Spain 2012 234 239

4. Steganalysis by subtractive pixel adjacency matrix;Pevny;IEEE Transactions on Information Forensics and Security,2010

5. Rich models for steganalysis of digital images;Fridrich;IEEE Transactions on Information Forensics and Security,2012

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1. Digital image steganalysis using entropy driven deep neural network;Journal of Information Security and Applications;2024-08

2. Pooled Steganalysis via Model Discrepancy;Mathematics;2024-02-11

3. High-Pass-Kernel-Driven Content-Adaptive Image Steganalysis Using Deep Learning;Mathematics;2023-10-17

4. Secure Steganographic Cover Generation via a Noise-Optimization Stacked StyleGAN2;Symmetry;2023-04-25

5. Identification of Content-Adaptive Image Steganography Using Convolutional Neural Network Guided by High-Pass Kernel;Applied Sciences;2022-11-21

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