Trajectory Data Semi-fragile Watermarking Algorithm Considering Spatiotemporal Features

被引:0
|
作者
Hu, Yuchen [1 ,2 ,3 ]
Zhu, Changqing [1 ,2 ,3 ]
Ren, Na [1 ,2 ,3 ]
Gu, Jinjie [1 ,2 ,3 ]
机构
[1] Nanjing Normal Univ, Key Lab Virtual Geog Environm, Minist Educ, Nanjing, Peoples R China
[2] State Key Lab Cultivat Base Geog Environm Evolut, Nanjing, Peoples R China
[3] Jiangsu Ctr Collaborat Innovat Geog Informat Reso, Nanjing, Peoples R China
来源
SPATIAL DATA AND INTELLIGENCE, SPATIALDI 2024 | 2024年 / 14619卷
关键词
Trajectory Data; Integrity of Spatiotemporal Features; Semi-fragile Watermark; Multiple Quantization Index Modulation; Tampering Detection;
D O I
10.1007/978-981-97-2966-1_23
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The high privacy and accuracy of trajectory data make data integrity and security critical. However, existing algorithms cannot ensure the integrity of temporal attributes and resist common operations in the normal use of data, which limits the use of data. For this reason, this paper proposes a semi-fragile water-marking algorithm for trajectory data that takes into account spatiotemporal features. The proposed algorithm utilizes the minimum area bounded rectangle (MABR) to group the trajectory data. Finally, the fragile watermarks generated from spatial and temporal attributes are embedded into an embedded domain with geometric invariance in stages using the multiple quantization index modulation (MQIM) technique. Experimental results show that the proposed algorithm is extremely robust to geometric attacks. Meanwhile, it can accurately identify whether the temporal and spatial attributes have been tampered with and the type of tampering. The proposed algorithm balances robustness and tampering detection capability, providing a feasible solution for the security protection of trajectory data.
引用
收藏
页码:319 / 332
页数:14
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