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TrajGuard: A Comprehensive Trajectory Copyright Protection Scheme

Published: 25 July 2019 Publication History

Abstract

Trajectory data has been widely used in many urban applications. Sharing trajectory data with effective supervision is a vital task, as it contains private information of moving objects. However, malicious data users can modify trajectories in various ways to avoid data distribution tracking by the hashing-based data signatures, e.g., MD5. Moreover, the existing trajectory data protection scheme can only protect trajectories from either spatial or temporal modifications. Finally, so far there is no authoritative third party for trajectory data sharing process, as trajectory data is too sensitive. To this end, we propose a novel trajectory copyright protection scheme, which can protect trajectory data from comprehensive types of data modifications/attacks. Three main techniques are employed to effectively guarantee the robustness and comprehensiveness of the proposed data sharing scheme: 1) the identity information is embedded distributively across a set of sub-trajectories partitioned based on the spatio-temporal regions; 2) the centroid distance of the sub-trajectories is served as a stable trajectory attribute to embed the information; and 3) the blockchain technique is used as a trusted third party to log all data transaction history for data distribution tracking in a decentralized manner. Extensive experiments were conducted based on two real-world trajectory datasets to demonstrate the effectiveness of our proposed scheme.

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Cited By

View all
  • (2024)RE-Trace: Re-identification of Modified GPS TrajectoriesACM Transactions on Spatial Algorithms and Systems10.1145/364368010:4(1-28)Online publication date: 5-Feb-2024
  • (2024)Moment invariants based zero watermarking algorithm for trajectory dataJournal of Information Security and Applications10.1016/j.jisa.2024.10386786:COnline publication date: 1-Nov-2024
  • (2024)A dual watermarking algorithm for trajectory data based on robust watermarking and fragile watermarkingComputers & Geosciences10.1016/j.cageo.2024.105655191:COnline publication date: 1-Sep-2024
  • Show More Cited By

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    cover image ACM Conferences
    KDD '19: Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
    July 2019
    3305 pages
    ISBN:9781450362016
    DOI:10.1145/3292500
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 25 July 2019

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    Author Tags

    1. copyright protection
    2. trajectory data
    3. urban computing

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    • Research-article

    Funding Sources

    • Shanghai Sailing Program
    • National Natural Science Foundation of China Grant

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    KDD '19 Paper Acceptance Rate 110 of 1,200 submissions, 9%;
    Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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    Cited By

    View all
    • (2024)RE-Trace: Re-identification of Modified GPS TrajectoriesACM Transactions on Spatial Algorithms and Systems10.1145/364368010:4(1-28)Online publication date: 5-Feb-2024
    • (2024)Moment invariants based zero watermarking algorithm for trajectory dataJournal of Information Security and Applications10.1016/j.jisa.2024.10386786:COnline publication date: 1-Nov-2024
    • (2024)A dual watermarking algorithm for trajectory data based on robust watermarking and fragile watermarkingComputers & Geosciences10.1016/j.cageo.2024.105655191:COnline publication date: 1-Sep-2024
    • (2024)Trajectory Data Semi-fragile Watermarking Algorithm Considering Spatiotemporal FeaturesSpatial Data and Intelligence10.1007/978-981-97-2966-1_23(319-332)Online publication date: 25-Apr-2024
    • (2023)Mobility trajectory generation: a surveyArtificial Intelligence Review10.1007/s10462-023-10598-x56:Suppl 3(3057-3098)Online publication date: 1-Dec-2023
    • (2022)W-traceProceedings of the 30th International Conference on Advances in Geographic Information Systems10.1145/3557915.3561474(1-4)Online publication date: 1-Nov-2022
    • (2020)Semantic-aware Spatio-temporal App Usage Representation via Graph Convolutional NetworkProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/34118174:3(1-24)Online publication date: 4-Sep-2020

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