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A Robust Zero-Watermarking Algorithm for Spatiotemporal Trajectory Data Protection
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AI
DOI：10.1002/cpe.70280.png)
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Abstract
En 中文
As an important type of spatiotemporal big data, trajectory data faces severe challenges such as illegal copying and dissemination, which infringes upon the legitimate rights of copyright owners. Existing copyright protection methods for trajectory data oftenregard it as a collection of points for watermark embedding, ignoring its inherent spatiotemporal characteristics. These method sex hi bit limitations in both robustness and specificity. To address this, this paper introduces a zero-watermarking algorithm for trajectory data that effectively integrates spatiotemporal features. The proposed algorithm begins by segmenting the trajectory intosub-trajectories using stay areas as key nodes, extracting feature points accordingly. Then, a watermark index is constructed based on the movement speed of each sub-trajectory in the X-direction, with the watermark information generated through a voting mechanism. Finally, an exclusive-O Ring (XOR) operation is performed between the watermark information and the scrambled copyright image to produce the zero-watermark image. Experimental results demonstrate that the proposed method exhibits strong robustness, effectively resisting various attacks such as time shifting, cropping, and coordinate point deletion. Specifically, thenormalized correlation (NC) value remains above 0.95 even when 50%of the coordinate points are removed, and achieves an N C value of 1.00 under geometric attacks including translation and scaling. Compared to existing watermarking schemes for trajectorydata, the proposed approach exhibits significantly enhanced robustness
Keywords:
copyright protection
lossless
spatiotemporal characteristics
trajectory data
zero-watermarking
Journal
C
IF:
1.5
Papers:
473
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0