使用生成对抗网络来对抗隐写分析

IF 0.6 Q4 AUTOMATION & CONTROL SYSTEMS

AUTOMATIC CONTROL AND COMPUTER SCIENCES Pub Date : 2025-03-14 DOI:10.3103/S0146411624700937

E. B. Aleksandrova, A. I. Bezborodko, D. S. Lavrova

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引用次数: 0

摘要

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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

The Use of Generative-Adversarial Networks to Counter Steganalysis

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The Use of Generative-Adversarial Networks to Counter Steganalysis

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.

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来源期刊

AUTOMATIC CONTROL AND COMPUTER SCIENCES AUTOMATION & CONTROL SYSTEMS-

CiteScore

1.70

自引率

22.20%

发文量

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