Abstract
Zero watermarking does not alter the original information contained in vector map data and provides perfect imperceptibility. The use of zero watermarking for data copyright protection has become a significant trend in digital watermarking research. However, zero watermarking encounters tremendous obstacles to its development and application because of its requirement to store copyright information with a third party and its difficulty in confirming copyright ownership. Aiming at the shortcomings of the existing zero watermarking technology, this paper proposes a new zero watermarking construction method based on the angular features of vector data that store the zero watermarking and copyright information on the blockchain after an XOR operation. When the watermark is being extracted, the copyright information can be extracted with the XOR operation to obtain the information stored on the blockchain. Experimental results show that the combination of zero watermarking and blockchain proposed in this paper gives full play to the advantages of the two technologies and protects the copyright of data in a lossless fashion. Compared with the traditional zero watermarking algorithms, the proposed zero watermarking algorithm exhibits stronger robustness. Moreover, the proposed data copyright protection framework with a combination of zero watermarking and blockchain can also be applied to other data types, such as images, audio, video, and remote sensing images.
Highlights
Vector data are widely used in the geographic information industry
Adding attacks are related to cropping attacks, where the Cropping and adding are standard data processing methods for vector data
The existing zero watermarking algorithm has the disadvantages of a long audit cycle, easy copyright loss, and difficult copyright ownership confirmation due to the requirement of copyright authentication by the intellectual property rights (IPR)
Summary
Vector data are widely used in the geographic information industry. Because of the small amount of data stored in vectors, as well as their fast updates and ease of copying and distribution, such data is vulnerable to illegal infringement and embezzlement. The existing digital watermark algorithms for vector data are mainly divided into spatial domain [2,3,4] and frequency domain [5,6] algorithms. These two types of methods embed watermark information by modifying coordinate values directly or indirectly. For vector data with high data accuracy requirements, the destruction of accuracy will directly reduce the data quality [7] Under this circumstance, lossless watermark technology can provide copyright protection without losing the original data’s accuracy, so it has more advantages than the traditional watermark. Lossless copyright protection technology for vector data has become a research focus in data security
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