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Adaptive Image Steganographic Analysis System Based on Deep Convolutional Neural Network

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成果类型:
会议论文
作者:
Jiao G.
作者机构:
College of Computer Science and Technology, Hengyang Normal University, Hengyang, Hunan 421002, China
Hunan Provincial Key Laboratory of Intelligent Information Processing and Application, Hengyang, Hunan 421002, China
语种:
英文
关键词:
Complex networks;Computational complexity;Convolution;Convolutional neural networks;Deep neural networks;Extraction;Image analysis;Learning algorithms;Steganography;Textures;Adaptive images;Analysis method;Analysis system;Convolutional neural network;Deep learning;Design features;Features extraction;Image steganographic analyse;Image steganography;Texture area;Feature extraction
期刊:
Lecture Notes in Electrical Engineering
ISSN:
1876-1100
年:
2022
卷:
808 LNEE
页码:
66-74
会议名称:
11th International Conference on Computer Engineering and Networks, CENet2021
会议时间:
21 October 2021 through 25 October 2021
出版者:
Springer Science and Business Media Deutschland GmbH
ISBN:
9789811665530
基金类别:
Acknowledgement. This work is supported by the Scientific Research Fund of Hunan Provincial Education Department (19B082), the Science and Technology Development Center of the Ministry of Education-New Generation Information Technology Innovation Project (2018A02020), the research supported by Science Foundation of Hengyang Normal University (19QD12), the Science and Technology Plan Project of Hunan Province (2016TP1020), the Application-oriented Special Disciplines, Double First-Class University Project of Hunan Province (Xiangjiaotong [2018] 469), the Hunan Province Special Funds of Central Government for Guiding Local Science and Technology Development (2018CT5001), the Subject Group Construction Project of Hengyang Normal University (18XKQ02), the First Class Undergraduate Major in Hunan Province – Internet of Things Major (Xiangjiaotong [2020] 248, No. 288).
机构署名:
本校为第一机构
院系归属:
计算机科学与技术学院
摘要:
Adaptive steganography emplaces the message into the hard-to-detect noise area or the complex texture area of the image, so the steganography analysis method based on artificial design features needs to design a very complex feature extraction algorithm to detect the steganography image. In view of the advantages of deep learning steganography in automatic extraction of image features and high detection accuracy, an image steganography analysis algorithm is designed by using deep convolutional neural network, and an image steganography analysis...

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