The Use of Generative-Adversarial Networks to Counter Steganalysis

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS
E. B. Aleksandrova, A. I. Bezborodko, D. S. Lavrova
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引用次数: 0

Abstract

An approach using a generative adversarial network (GAN) is proposed to increase the robustness of the steganographic method against modern steganalyzers. This approach is based on the combined operation of a GAN, a pixel importance map, and the least significant bit (LSB) substitution method. The results of the experimental studies confirmed the effectiveness of the proposed approach.

Abstract Image

使用生成对抗网络来对抗隐写分析
提出了一种使用生成对抗网络(GAN)的方法来提高隐写方法对现代隐写分析器的鲁棒性。该方法是基于GAN、像素重要性图和最低有效位(LSB)替换法的组合操作。实验研究结果证实了该方法的有效性。
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来源期刊
AUTOMATIC CONTROL AND COMPUTER SCIENCES
AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.70
自引率
22.20%
发文量
47
期刊介绍: Automatic Control and Computer Sciences is a peer reviewed journal that publishes articles on• Control systems, cyber-physical system, real-time systems, robotics, smart sensors, embedded intelligence • Network information technologies, information security, statistical methods of data processing, distributed artificial intelligence, complex systems modeling, knowledge representation, processing and management • Signal and image processing, machine learning, machine perception, computer vision
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