A Survey on Deep Convolutional Neural Networks for Image Steganography and Steganalysis

• Israr Hussain,
• Jishen Zeng,
• Xinhong,
• Shunquan Tan,

Vol. 14, No. 3, March 31, 2020
10.3837/tiis.2020.03.017, Download Paper (Free):

• Steganalysis
• Steganography
• Deep Learning
• Convolutional Neural Network

Abstract

Steganalysis & steganography have witnessed immense progress over the past few years by the advancement of deep convolutional neural networks (DCNN). In this paper, we analyzed current research states from the latest image steganography and steganalysis frameworks based on deep learning. Our objective is to provide for future researchers the work being done on deep learning-based image steganography & steganalysis and highlights the strengths and weakness of existing up-to-date techniques. The result of this study opens new approaches for upcoming research and may serve as source of hypothesis for further significant research on deep learning-based image steganography and steganalysis. Finally, technical challenges of current methods and several promising directions on deep learning steganography and steganalysis are suggested to illustrate how these challenges can be transferred into prolific future research avenues.

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