W-trace: robust and effective watermarking for GPS trajectories

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

  • Rajjat Dadwal
  • Thorben Funke
  • Michael Nüsken
  • Elena Demidova

Research Organisations

External Research Organisations

  • Bonn-Aachen International Center for Information Technology (b-it)
  • University of Bonn
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Details

Original languageEnglish
Title of host publication30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Subtitle of host publicationACM SIGSPATIAL GIS 2022
EditorsMatthias Renz, Mohamed Sarwat, Mario A. Nascimento, Shashi Shekhar, Xing Xie
PublisherAssociation for Computing Machinery (ACM)
ISBN (electronic)9781450395298
Publication statusPublished - 22 Nov 2022
Event30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2022 - Seattle, United States
Duration: 1 Nov 20224 Nov 2022

Publication series

NameGIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems

Abstract

With the rise of data-driven methods for traffic forecasting, accident prediction, and profiling driving behavior, personal GPS trajectory data has become an essential asset for businesses and emerging data markets. However, as personal data, GPS trajectories require protection. Especially by data breaches, verification of GPS data ownership is a challenging problem. Watermarking facilitates data ownership verification by encoding provenance information into the data. GPS trajectory watermarking is particularly challenging due to the spatio-temporal data properties and easiness of data modification; as a result, existing methods embed only minimal provenance information and lack robustness. In this paper, we propose W-Trace-a novel GPS trajectory watermarking method based on Fourier transformation. We demonstrate the effectiveness and robustness of W-Trace on two real-world GPS trajectory datasets.

Keywords

    data protection, data provenance, GPS trajectory, watermarking

ASJC Scopus subject areas

Cite this

W-trace: robust and effective watermarking for GPS trajectories. / Dadwal, Rajjat; Funke, Thorben; Nüsken, Michael et al.
30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022. ed. / Matthias Renz; Mohamed Sarwat; Mario A. Nascimento; Shashi Shekhar; Xing Xie. Association for Computing Machinery (ACM), 2022. 77 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Dadwal, R, Funke, T, Nüsken, M & Demidova, E 2022, W-trace: robust and effective watermarking for GPS trajectories. in M Renz, M Sarwat, MA Nascimento, S Shekhar & X Xie (eds), 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022., 77, GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems, Association for Computing Machinery (ACM), 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2022, Seattle, United States, 1 Nov 2022. https://doi.org/10.48550/arXiv.2211.08116, https://doi.org/10.1145/3557915.3561474
Dadwal, R., Funke, T., Nüsken, M., & Demidova, E. (2022). W-trace: robust and effective watermarking for GPS trajectories. In M. Renz, M. Sarwat, M. A. Nascimento, S. Shekhar, & X. Xie (Eds.), 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022 Article 77 (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). Association for Computing Machinery (ACM). https://doi.org/10.48550/arXiv.2211.08116, https://doi.org/10.1145/3557915.3561474
Dadwal R, Funke T, Nüsken M, Demidova E. W-trace: robust and effective watermarking for GPS trajectories. In Renz M, Sarwat M, Nascimento MA, Shekhar S, Xie X, editors, 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022. Association for Computing Machinery (ACM). 2022. 77. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems). doi: 10.48550/arXiv.2211.08116, 10.1145/3557915.3561474
Dadwal, Rajjat ; Funke, Thorben ; Nüsken, Michael et al. / W-trace : robust and effective watermarking for GPS trajectories. 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022. editor / Matthias Renz ; Mohamed Sarwat ; Mario A. Nascimento ; Shashi Shekhar ; Xing Xie. Association for Computing Machinery (ACM), 2022. (GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems).
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title = "W-trace: robust and effective watermarking for GPS trajectories",
abstract = "With the rise of data-driven methods for traffic forecasting, accident prediction, and profiling driving behavior, personal GPS trajectory data has become an essential asset for businesses and emerging data markets. However, as personal data, GPS trajectories require protection. Especially by data breaches, verification of GPS data ownership is a challenging problem. Watermarking facilitates data ownership verification by encoding provenance information into the data. GPS trajectory watermarking is particularly challenging due to the spatio-temporal data properties and easiness of data modification; as a result, existing methods embed only minimal provenance information and lack robustness. In this paper, we propose W-Trace-a novel GPS trajectory watermarking method based on Fourier transformation. We demonstrate the effectiveness and robustness of W-Trace on two real-world GPS trajectory datasets.",
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N1 - Funding Information: This work is partially funded by the Federal Ministry for Economic Affairs and Climate Action (BMWK), Germany, under “CampaNeo” (01MD19007B), and “d-E-mand” (01ME19009B), the European Commission (EU H2020) under “smashHit” (871477), the German Research Foundation under “WorldKG” (424985896), and by the B-IT foundation and the state of North Rhine-Westphalia (Germany).

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AB - With the rise of data-driven methods for traffic forecasting, accident prediction, and profiling driving behavior, personal GPS trajectory data has become an essential asset for businesses and emerging data markets. However, as personal data, GPS trajectories require protection. Especially by data breaches, verification of GPS data ownership is a challenging problem. Watermarking facilitates data ownership verification by encoding provenance information into the data. GPS trajectory watermarking is particularly challenging due to the spatio-temporal data properties and easiness of data modification; as a result, existing methods embed only minimal provenance information and lack robustness. In this paper, we propose W-Trace-a novel GPS trajectory watermarking method based on Fourier transformation. We demonstrate the effectiveness and robustness of W-Trace on two real-world GPS trajectory datasets.

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