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Current trends in the field of steganalysis and guidelines for constructions of new steganalysis schemes
PublicationThe paper concerns blind steganalysis techniques in the passive steganalysis scenario designed to detect the steganographic cover modification schemes. The goal is to investigate the state-of-art in the field of steganalysis, and, above all, to recognize current trends existing in this field and determine guidelines for constructions of new steganalysis schemes. The intended effects are to examine the possibilities for the development...
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Architectural Modifications to Enhance Steganalysis with Convolutional Neural Networks
PublicationThis paper investigates the impact of various modifications introduced to current state-of-the-art Convolutional Neural Network (CNN) architectures specifically designed for the steganalysis of digital images. Usage of deep learning methods has consistently demonstrated improved results in this field over the past few years, primarily due to the development of newer architectures with higher classification accuracy compared to...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublicationThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...