Damageless Digital Watermarking by Machine Learning: A Method of Key Generation for Information Extraction Using Artificial Neural Networks
Damageless Digital Watermarking by Machine Learning: A Method of Key Generation for Information Extraction Using Artificial Neural Networks
复制标题
机器学习无损数字水印：一种使用人工神经网络进行信息提取的密钥生成方法
DOI：
10.1109/socpar.2009.109
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发表时间：
2009
期刊：
影响因子：
--
通讯作者：
Yoshiyasu Takefuji
中科院分区：
文献类型：
--
作者：
Kensuke Naoe;H. Sasaki;Yoshiyasu Takefuji
信息安全领域的软计算是创建智能解决方案的一个很有前途的领域。讨论了一种利用人工神经网络进行数字水印的方法，以实现对视觉信息的安全版权保护。讨论的水印提取密钥和特征提取密钥识别用于适当的数字水印的安全且唯一的隐藏模式。实验表明，该方法对高通滤波和JPEG压缩视频信息具有较好的鲁棒性，只适用于那些能够利用相应的特征提取密钥从原始视频信息中识别出合适的隐藏位模式的水印提取密钥。提出的方法是在不破坏或丢失任何视觉信息详细数据的情况下，为安全的视觉数字水印做出贡献。
Soft computing in the area of information security is a promising field for the creation of intelligent solutions. This paper discusses a method for digital watermarking using artificial neural networks to realize secure copyright protection of visual information without any damage. The discussed watermark extraction keys and feature extraction keys identify the secure and unique hidden patterns for proper digital watermarks. In the experiments, we have shown that the proposed method is robust to high pass filtering and JPEG compression of visual information, only for those watermark extraction keys which were able to identify the proper hidden bit patterns from original visual information using corresponding feature extraction keys. The proposed method is to contribute to secure visual digital watermarking without damaging or losing any detailed data of visual information.