基于半脆弱水印的隐写攻击检测类型研究

M. N. Isaeva
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引用次数: 1

摘要

本文讨论了如何使用机器学习技术检测使用半脆弱水印的数字图像的隐写攻击类型。本文讨论了在空间域和变换域引入水印的不同方法。在这种情况下,攻击是可以应用于图像的过滤器:模糊,添加噪点,清晰度,对比度,色彩平衡。已经确定了一些方法,使您能够更准确地确定对图像中嵌入的数字水印的特定攻击类型。该方法的特点是不需要使用原始图像来确定攻击(盲法[1])。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detection Types of Steganographic Attacks Based on Semi-Fragile Watermarks Using Machine Learning
This article discusses how to detected types of steganographic attacks on digital images using semi-fragile watermarks using machine learning techniques. This article discusses different methods of introducing watermarks: into the spatial domain and the transformation domain. The attacks in this case are filters that can be applied to images: blurring, adding noise, sharpness, contrast, color balance. Methods have been identified that allow you to determine with higher accuracy the specific type of attack on the embedded digital watermark in the image. The peculiarity of this method is that the original image does not need to be used to determine the attack (blind method [1]).
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