Convolution Neural Networks for Blind Image Steganalysis: A Comprehensive Study

  • Mohsin Ahmed H
  • Hasan Mahmoud H
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Abstract

Recently, Convolution Neural Network is widely applied in Image Classification, Object Detection, Scene labeling, Speech, Natural Language Processing and other fields. In this comprehensive study a variety of scenarios and efforts are surveyed since 2014 at yet, in order to provide a guide to further improve future researchers what CNN-based blind image steganalysis are presented its architecture, performance and limitations. Long-standing and important problem in image steganalysis difficulties mainly lie in how to give high accuracy and low payload in stego or cover images for improving performance of the network.

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Mohsin Ahmed, H., & Hasan Mahmoud, H. (2019). Convolution Neural Networks for Blind Image Steganalysis: A Comprehensive Study. Journal of Al-Qadisiyah for Computer Science and Mathematics, 11(2), 53–64. https://doi.org/10.29304/jqcm.2019.11.2.573

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