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Robust Hashing of Vector Data Using Generalized Curvatures of Polyline

机译:使用折线的广义曲率对向量数据进行强健的散列

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摘要

With the rapid expansion of vector data model application to digital content such as drawings and digital maps, the security and retrieval for vector data models have become an issue. In this paper, we present a vector data-hashing algorithm for the authentication, copy protection, and indexing of vector data models that are composed of a number of layers in CAD family formats. The proposed hashing algorithm groups polylines in a vector data model and generates group coefficients by the curvatures of the first and second type of polylines. Subsequently, we calculate the feature coefficients by projecting the group coefficients onto a random pattern, and finally generate the binary hash from binarization of the feature coefficients. Based on experimental results using a number of drawings and digital maps, we verified the robustness of the proposed hashing algorithm against various attacks and the uniqueness and security of the random key.
机译:随着矢量数据模型的应用迅速扩展到数字内容(例如图形和数字地图),矢量数据模型的安全性和检索已成为一个问题。在本文中,我们提出了一种矢量数据哈希算法,用于矢量数据模型的身份验证,复制保护和索引编制,该矢量数据模型由CAD系列格式的许多层组成。所提出的散列算法在矢量数据模型中对折线进行分组,并通过第一和第二种折线的曲率生成分组系数。随后,我们通过将组系数投影到随机图案上来计算特征系数,最后通过特征系数的二值化生成二进制哈希。基于使用大量图形和数字地图的实验结果,我们验证了所提出的哈希算法针对各种攻击的鲁棒性以及随机密钥的唯一性和安全性。

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