抵抗去同步攻击的鲁棒水印技术研究
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摘要
伴随着数字媒体、因特网、云端计算等信息技术的迅猛发展以及廉价计算终端的快速普及,各种网络多媒体信息服务也得到了长足的发展。这些先进的信息技术为广大人民带来方便的同时,也给盗版者提供了便利,从而威胁版权所有者的合法权益。作为数字版权保护的技术手段之一,数字水印技术得到了学术界和工业界的广泛关注。
随着数字水印技术的发展,针对水印的攻击技术也在不断发展,设计鲁棒的水印算法也变得越来越困难。尤其是去同步攻击,对数字水印是一巨大威胁。针对如何抵抗去同步攻击这一关键问题,本论文取得的创新性研究成果包括：
为抵抗全局去同步攻击,本文利用具有全局不变性的几何不变区域进行水印重同步。首先,提出了一种几何不变区域的检测算法。然后,提出了一种鲁棒的扇形区域划分方法用于划分图像中的每个几何不变区域。水印的嵌入和提取过程都以扇形区域为参考,从而达到水印重同步的目的。大量的实验结果都验证了该算法的鲁棒性。
为抵抗局部去同步攻击,本文提出了一种基于局部几何不变特征的水印重同步算法。首先,提出了一种具有局部几何不变性的特征变换LDFT (local daisy feature transform),将图像的所有像素点都变换到几何不变的LDFT特征空间。然后,通过构建BSP (binary space partitioning)树来划分LDFT特征空间。由于去同步攻击前后,像素点在BSP树上的位置不变,因此可以利用构造的BSP树来进行水印的重同步。最后,通过实验以及与相关算法的比较证明了该算法的鲁棒性。
为抵抗不可逆的去同步攻击,本文首先提出了一种新的图像显著性检测模型。该模型有效地融合了图像的自底向上和自顶向下的特征。为验证该模型的有效性,在现有的两个最大的公开数据集上与13个现有模型进行了比较。定量和定性的实验都验证了本文所设计显著性检测模型的有效性。一般情况下,图像的显著区域在遭受目标重定位这种不可逆的去同步攻击后不会被删除,故可以作为水印嵌入和提取位置的重要参考。最后的实验也验证了本文所提算法对这种攻击的鲁棒性。
Digital media widely spread along with the booming development of computer sci-ence, Internet of Things, cloud computing and the Internet technology. However, unre-stricted reproduction and convenient manipulation of digital media cause considerable economic losses to the media creators and the content providers. Therefore, digital wa-termarking is introduced to prevent the above infringement.
In the past ten years, attacks against image watermarking systems have become in-creasingly complicated with the development of watermarking techniques. Up to now, a watermarking scheme that is robust against desynchronization attacks is still a grand chal-lenge. Desynchronization attacks can be classified into three categories:global desyn-chronization attacks and local desynchronization attacks, and non-invertible desynchro-nization attacks. In order to resist this three kinds of desynchronization, we proposed three watermarking resynchronization schemes in this dissertation.
In order to resist global desynchronization attacks, we proposed a new watermark-ing resynchronization scheme based on GIRs (geometric-invariant regions). First, we introduced a novel GIRs detection method that is implemented by robust edge contours extraction, robust corners detection, and the radius selection. Then, we designed a new sector-shaped partitioning method for GIR. The sector-shaped partitioning is invariable to geometric transforms, so the sequence of sectors will not be out-of-order under ge-ometric transforms. The GIRs and the divided sector discs are invariant to geometric transforms, so the watermarking method inherently has high robustness against global desynchronization attacks as shown in experiments.
We presented a blind image watermarking resynchronization scheme against local transform attacks. Firstly, we propose a new feature transform named local daisy feature transform (LDFT), which is not only globally but also locally invariable. Then the binary space partitioning (BSP) tree is used to partition the geometrically invariant LDFT space. In the BSP tree, the location of each pixel is fixed under global transform, local transform, and cropping. Lastly, the watermarking sequence is embedded bit by bit into each leaf-node of the BSP tree by using the logarithmic quantization index modulation (LQIM) watermarking embedding method.
In order to resist non-invertible desynchronization attacks, we proposed a novel two- stage saliency detection model by fusing bottom-up and up-down features extracted from a single image in this dissertation. The evaluation of the proposed model has been carried out on two largest publicly available data sets. As indicated in the experimental results, the proposed model consistently outperforms13existing saliency detection methods with higher precision and better recall rates. The watermarking resynchronization scheme is proposed based on the salient region of the image. Because the salient region will not be cropped when the image is attacked by non-invertible desynchronization attacks (such as:image retargeting), the proposed the watermarking scheme is robust against the non-invertible desynchronization attack.
随着数字水印技术的发展,针对水印的攻击技术也在不断发展,设计鲁棒的水印算法也变得越来越困难。尤其是去同步攻击,对数字水印是一巨大威胁。针对如何抵抗去同步攻击这一关键问题,本论文取得的创新性研究成果包括：
为抵抗全局去同步攻击,本文利用具有全局不变性的几何不变区域进行水印重同步。首先,提出了一种几何不变区域的检测算法。然后,提出了一种鲁棒的扇形区域划分方法用于划分图像中的每个几何不变区域。水印的嵌入和提取过程都以扇形区域为参考,从而达到水印重同步的目的。大量的实验结果都验证了该算法的鲁棒性。
为抵抗局部去同步攻击,本文提出了一种基于局部几何不变特征的水印重同步算法。首先,提出了一种具有局部几何不变性的特征变换LDFT (local daisy feature transform),将图像的所有像素点都变换到几何不变的LDFT特征空间。然后,通过构建BSP (binary space partitioning)树来划分LDFT特征空间。由于去同步攻击前后,像素点在BSP树上的位置不变,因此可以利用构造的BSP树来进行水印的重同步。最后,通过实验以及与相关算法的比较证明了该算法的鲁棒性。
为抵抗不可逆的去同步攻击,本文首先提出了一种新的图像显著性检测模型。该模型有效地融合了图像的自底向上和自顶向下的特征。为验证该模型的有效性,在现有的两个最大的公开数据集上与13个现有模型进行了比较。定量和定性的实验都验证了本文所设计显著性检测模型的有效性。一般情况下,图像的显著区域在遭受目标重定位这种不可逆的去同步攻击后不会被删除,故可以作为水印嵌入和提取位置的重要参考。最后的实验也验证了本文所提算法对这种攻击的鲁棒性。
Digital media widely spread along with the booming development of computer sci-ence, Internet of Things, cloud computing and the Internet technology. However, unre-stricted reproduction and convenient manipulation of digital media cause considerable economic losses to the media creators and the content providers. Therefore, digital wa-termarking is introduced to prevent the above infringement.
In the past ten years, attacks against image watermarking systems have become in-creasingly complicated with the development of watermarking techniques. Up to now, a watermarking scheme that is robust against desynchronization attacks is still a grand chal-lenge. Desynchronization attacks can be classified into three categories:global desyn-chronization attacks and local desynchronization attacks, and non-invertible desynchro-nization attacks. In order to resist this three kinds of desynchronization, we proposed three watermarking resynchronization schemes in this dissertation.
In order to resist global desynchronization attacks, we proposed a new watermark-ing resynchronization scheme based on GIRs (geometric-invariant regions). First, we introduced a novel GIRs detection method that is implemented by robust edge contours extraction, robust corners detection, and the radius selection. Then, we designed a new sector-shaped partitioning method for GIR. The sector-shaped partitioning is invariable to geometric transforms, so the sequence of sectors will not be out-of-order under ge-ometric transforms. The GIRs and the divided sector discs are invariant to geometric transforms, so the watermarking method inherently has high robustness against global desynchronization attacks as shown in experiments.
We presented a blind image watermarking resynchronization scheme against local transform attacks. Firstly, we propose a new feature transform named local daisy feature transform (LDFT), which is not only globally but also locally invariable. Then the binary space partitioning (BSP) tree is used to partition the geometrically invariant LDFT space. In the BSP tree, the location of each pixel is fixed under global transform, local transform, and cropping. Lastly, the watermarking sequence is embedded bit by bit into each leaf-node of the BSP tree by using the logarithmic quantization index modulation (LQIM) watermarking embedding method.
In order to resist non-invertible desynchronization attacks, we proposed a novel two- stage saliency detection model by fusing bottom-up and up-down features extracted from a single image in this dissertation. The evaluation of the proposed model has been carried out on two largest publicly available data sets. As indicated in the experimental results, the proposed model consistently outperforms13existing saliency detection methods with higher precision and better recall rates. The watermarking resynchronization scheme is proposed based on the salient region of the image. Because the salient region will not be cropped when the image is attacked by non-invertible desynchronization attacks (such as:image retargeting), the proposed the watermarking scheme is robust against the non-invertible desynchronization attack.
引文
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