Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems |
| Untertitel | ACM SIGSPATIAL GIS 2022 |
| Herausgeber/-innen | Matthias Renz, Mohamed Sarwat, Mario A. Nascimento, Shashi Shekhar, Xing Xie |
| Herausgeber (Verlag) | Association for Computing Machinery (ACM) |
| ISBN (elektronisch) | 9781450395298 |
| Publikationsstatus | Veröffentlicht - 22 Nov. 2022 |
| Veranstaltung | 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2022 - Seattle, USA / Vereinigte Staaten Dauer: 1 Nov. 2022 → 4 Nov. 2022 |
Publikationsreihe
| Name | GIS: 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.
ASJC Scopus Sachgebiete
- Erdkunde und Planetologie (insg.)
- Erdoberflächenprozesse
- Informatik (insg.)
- Angewandte Informatik
- Mathematik (insg.)
- Modellierung und Simulation
- Informatik (insg.)
- Computergrafik und computergestütztes Design
- Informatik (insg.)
- Information systems
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- BibTex
- RIS
30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems: ACM SIGSPATIAL GIS 2022. Hrsg. / 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).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - W-trace
T2 - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, SIGSPATIAL GIS 2022
AU - Dadwal, Rajjat
AU - Funke, Thorben
AU - Nüsken, Michael
AU - Demidova, Elena
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).
PY - 2022/11/22
Y1 - 2022/11/22
N2 - 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.
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.
KW - data protection
KW - data provenance
KW - GPS trajectory
KW - watermarking
UR - http://www.scopus.com/inward/record.url?scp=85143604321&partnerID=8YFLogxK
U2 - 10.48550/arXiv.2211.08116
DO - 10.48550/arXiv.2211.08116
M3 - Conference contribution
AN - SCOPUS:85143604321
T3 - GIS: Proceedings of the ACM International Symposium on Advances in Geographic Information Systems
BT - 30th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
A2 - Renz, Matthias
A2 - Sarwat, Mohamed
A2 - Nascimento, Mario A.
A2 - Shekhar, Shashi
A2 - Xie, Xing
PB - Association for Computing Machinery (ACM)
Y2 - 1 November 2022 through 4 November 2022
ER -