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To address the variability and complexity of attack types, this paper proposes a multi-instance zero-watermarking algorithm that goes beyond the conventional one-to-one watermarking approach. Inspired by the class-instance paradigm in object-oriented programming, this algorithm constructs multiple zero watermarks from a single vector geographic dataset to enhance resilience against diverse attacks. Normalization is applied to eliminate dimensional and deformation inconsistencies, ensuring robustness against non-uniform scaling attacks. Feature triangle construction and angle selection are further utilized to provide resistance to interpolation and compression attacks. Moreover, angular features confer robustness against translation, uniform scaling, and rotation attacks. Experimental results demonstrate the superior robustness of the proposed algorithm, with normalized correlation values consistently maintaining 1.00 across various attack scenarios. Compared with existing methods, the algorithm exhibits superior comprehensive robustness, effectively safeguarding the copyright of vector geographic data.
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; Lin, Yan 2 ; Wang, Zihao 2 ; Ren, Na 3 ; Zhu, Changqing 4 1 School of Geoscience and Technology, Zhengzhou University, Zhengzhou 450001, China;
2 Hunan Engineering Research Center of Geographic Information Security and Application, Changsha 410017, China; The Third Surveying and Mapping Institute of Hunan Province, Changsha 410018, China
3 Hunan Engineering Research Center of Geographic Information Security and Application, Changsha 410017, China; Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China;
4 Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China;