research-article

A dummy-based anonymization method based on user trajectory with pauses

Authors:

Akiyoshi Suzuki,

Shojiro NishioAuthors Info & Claims

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

Pages 249 - 258

https://doi.org/10.1145/2424321.2424354

Published: 06 November 2012 Publication History

Abstract

A variety of services utilizing users' positions have become available because of rapid advances in Global Positioning System (GPS) technologies. Since location information may reveal private information, preserving location privacy has become a significant issue. We proposed a dummy-based method of anonymizing location to protect this privacy in our previous work that generated dummies based on various restrictions in a real environment. However, the previous work assumed a simplified mobility model in which users kept moving and did not stop. If we assume a more realistic mobility model in which users often pause to visit various attractions, it becomes increasingly more difficult to generate dummies that will move naturally. In this paper, we assumed that the users' movements are known in advance and propose a dummy-based anonymization method based on user movements, where dummies move naturally while stopping at several locations. We simulated user movements on real map information and verified the method we propose was more effective than the previous one.

References

[1]

C. A. Ardagna, M. Cremonini, E. Damiani, S. D. C. di Vimercati, and P. Samarati, "Location Privacy Protection through Obfuscation-Based Techniques," In Proc. DBSec, pp 47--60, 2007.

Digital Library

[2]

A. R. Beresford and F. Stajano, "Location Privacy in Pervasive Computing," In Proc. Pervasive, pp. 46--55, 2003.

[3]

C. Bettini, S. Mascetti, X. S. Wang, and S. Jajodia, "Anonymity in Location-Based Services, Towards a General Framework," In Proc. MDM, pp. 69--76, 2007.

Digital Library

[4]

R. W. Bohannon, "Comfortable and Maximal Walking Speed of Adults Aged 20--79 Years: Reference Values and Determinants," In: Age Ageing, pp. 12--19, 1997.

[5]

L. Busic, and R. Filjar, "The Role of Position Reporting Frequency in LBS Qos Establishment," In Proc. SoftCOM, pp. 209--213, 2006.

[6]

R. Cheng, Y. Zhang, E. Bertono, and S. Prabhakar, "Preserving User Location Privacy in Mobile Data Management Infrastructures," In Proc. PET, pp. 393--412, 2006.

Digital Library

[7]

C. Y. Chow, M. F. Mokbel, and X. Liu, "A Peer-to-Peer Spatial Cloaking Algorithm for Anonymous Location-Based Services," In Proc. GIS, pp. 171--178, 2006.

Digital Library

[8]

M. Duckham and L. Kulik, "A Formal Model of Obfuscation and Negotiation for Location Privacy," In Proc. PERVASIVE, pp. 152--170, 2005.

Digital Library

[9]

B. Gedik and L. Liu, "Location Privacy in Mobile Systems: A Personalized Anonymization Model," In Proc. ICDCS, pp. 620--629, 2005.

Digital Library

[10]

M. Gruteser and D. Grunwald, "Anonymous Usage of Location-based Services through Spatial and Temporal Cloaking," In Proc. ISENIX MobiSys, 2003.

Digital Library

[11]

A. Khoshgozaran, and C. Shahabi, "Blind Evaluation of Nearest Neighbor Queries Using Space Transformation to Preserve Location Privacy," In Proc. SSTD, pp. 239--257 2007.

Digital Library

[12]

H. Kido, Y. Yanagisawa, and T. Satoh, "An Anonymous Communication Technique using Dummies for Location-Based Service," In Proc. ICPS, pp. 88--97, 2005.

[13]

J. Krumm, "Realistic Driving Trips for Location Privacy," In Proc. PERVASIVE, pp. 25--41 2009.

Digital Library

[14]

H. Lu, C. S. Jensen, and M. L. Yiu, "PAD: Privacy-Area Aware, Dummy-Based Location Privacy in Mobile Services," In Proc. Int'l Workshop on Data Engineering for Wireless and Mobile Access, pp. 16--23, 2008.

Digital Library

[15]

M. Masanori, I. Yoshiharu, "Anonymizing User Location and Profile Information for Privacy-aware Mobile Services," In Proc. GIS-LBSN, pp. 69--75, 2010.

Digital Library

[16]

R. Shokri, J. Freudiger, M. Jadliwala, and J. P. Hubaux, "A Distortion-Based Metric for Location Privacy," In Proc. WPES, p. 6, 2009.

Digital Library

[17]

A. Suzuki, M. Iwata, Y. Arase, T. Hara, X. Xie, S. Nishio, "A User Location Anonymization Method for Location based Services in a Real Environment," In Proc. GIS, pp. 398--401, 2010.

Digital Library

[18]

Y. Yanagisawa, H. Kido, and T. Satoh, "Location Traceability of Users in Location-Based Services," In Proc. Int'l. Conf. on Mobile and Ubiquitous Computing, 2006.

[19]

L. Yao, G. Wu, J. Wang, F. Xia, C. Lin, G. Wang, "A Clustering KAnonymity Scheme for Location Privacy Preservation," In Journal on Trust, Security and Privacy in Computing and Communication Systems, Vol. 95--D, No. 1, pp. 134--142, 2012.

Cited By

Jin FHua WLi LRuan BZhou X(2024)Efficient Frequency-Based Randomization for Spatial Trajectories Under Differential PrivacyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3322471(1-14)Online publication date: 2024
https://doi.org/10.1109/TKDE.2023.3322471
Gupta AShanker U(2024)Location Privacy Preservation for Location Based Service Applications: Taxonomies, Issues and Future Research DirectionsWireless Personal Communications10.1007/s11277-024-10977-9134:3(1617-1639)Online publication date: 6-Apr-2024
https://doi.org/10.1007/s11277-024-10977-9
Zhang GZhao PZhang AZhang GZhao PZhang A(2024)Synthesizing Privacy-Preserving Traces: Enhancing Plausibility with Social NetworksPrivacy Preservation in Distributed Systems10.1007/978-3-031-58013-0_2(25-52)Online publication date: 8-Apr-2024
https://doi.org/10.1007/978-3-031-58013-0_2
Show More Cited By

Index Terms

A dummy-based anonymization method based on user trajectory with pauses
1. Computing methodologies
  1. Artificial intelligence
    1. Philosophical/theoretical foundations of artificial intelligence
      1. Cognitive science
2. Human-centered computing
  1. Human computer interaction (HCI)

Recommendations

A user location anonymization method for location based services in a real environment
GIS '10: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

Recent mobile devices are mostly equipped with a GPS receiver. This trend has arisen a variety of location based services (LBSs) which enable users to search local information of their current locations. To use LBSs, a user needs to send his/her ...
Dummy Generation-Based Privacy Preservation for Location-Based Services
ICDCN '20: Proceedings of the 21st International Conference on Distributed Computing and Networking

Location-Based Services (LBS) are a type of applications, which requires user's location information as input in providing useful services [4]. Google Maps (Online Navigation Applications), Foursquare (Geo-Social Network), Strava (Fitness Applications), ...
Feeling-based location privacy protection for location-based services
CCS '09: Proceedings of the 16th ACM conference on Computer and communications security

Anonymous location information may be correlated with restricted spaces such as home and office for subject re-identification. This makes it a great challenge to provide location privacy protection for users of location-based services. Existing work ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

SIGSPATIAL '12: Proceedings of the 20th International Conference on Advances in Geographic Information Systems

November 2012

642 pages

ISBN:9781450316910

DOI:10.1145/2424321

General Chairs:
Isabel Cruz
University of Illinois at Chicago
,
Craig Knoblock
University of Southern California
,
Program Chairs:
Peer Kröger
Ludwig-Maximilians-Universität München, Germany
,
Egemen Tanin
University of Melbourne, Australia
,
Peter Widmayer
ETH Zürich, Switzerland

Copyright © 2012 ACM.

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]

Sponsors

SIGSPATIAL: ACM Special Interest Group on Spatial Information

In-Cooperation

SIGGRAPH: ACM Special Interest Group on Computer Graphics and Interactive Techniques

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2012

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Research-article

Funding Sources

Microsoft Research Core Project and Grant-in-Aid for Exploratory Research
Microsoft Research

Conference

SIGSPATIAL'12

Sponsor:

SIGSPATIAL

SIGSPATIAL'12: SIGSPATIAL 2012 International Conference on Advances in Geographic Information Systems

November 6 - 9, 2012

Redondo Beach, California

Acceptance Rates

Overall Acceptance Rate 257 of 1,238 submissions, 21%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

56
Total Citations
View Citations
604
Total Downloads

Downloads (Last 12 months)18
Downloads (Last 6 weeks)6

Reflects downloads up to 07 Mar 2025

Other Metrics

View Author Metrics

Citations

Cited By

Jin FHua WLi LRuan BZhou X(2024)Efficient Frequency-Based Randomization for Spatial Trajectories Under Differential PrivacyIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2023.3322471(1-14)Online publication date: 2024
https://doi.org/10.1109/TKDE.2023.3322471
Gupta AShanker U(2024)Location Privacy Preservation for Location Based Service Applications: Taxonomies, Issues and Future Research DirectionsWireless Personal Communications10.1007/s11277-024-10977-9134:3(1617-1639)Online publication date: 6-Apr-2024
https://doi.org/10.1007/s11277-024-10977-9
Zhang GZhao PZhang AZhang GZhao PZhang A(2024)Synthesizing Privacy-Preserving Traces: Enhancing Plausibility with Social NetworksPrivacy Preservation in Distributed Systems10.1007/978-3-031-58013-0_2(25-52)Online publication date: 8-Apr-2024
https://doi.org/10.1007/978-3-031-58013-0_2
Sun HCao CChu XHu TLu JHe LWang ZHe HXiong H(2023)What Your Next Check-in Might Look Like: Next Check-in Behavior PredictionACM Transactions on Intelligent Systems and Technology10.1145/362523414:6(1-21)Online publication date: 14-Nov-2023
https://dl.acm.org/doi/10.1145/3625234
Li STian HShen HSang Y(2023)Differential-Privacy Preserving Trajectory Data Publishing for Road NetworksRecent Challenges in Intelligent Information and Database Systems10.1007/978-3-031-42430-4_46(558-571)Online publication date: 29-Sep-2023
https://doi.org/10.1007/978-3-031-42430-4_46
Zhu LLiu XJing ZYu LCai ZZhang J(2022)Knowledge-Driven Location Privacy Preserving Scheme for Location-Based Social NetworksElectronics10.3390/electronics1201007012:1(70)Online publication date: 24-Dec-2022
https://doi.org/10.3390/electronics12010070
Xudong YLing GYan LHairong ZQuanli GJie ZHai W(2022)A Blockchain-Based Location Privacy-Preserving Scheme in Location-Based ServiceMobile Information Systems10.1155/2022/19314512022Online publication date: 1-Jan-2022
https://dl.acm.org/doi/10.1155/2022/1931451
Zheng ZLi ZLi JJiang HLi TGuo B(2022)Utility-aware and Privacy-preserving Trajectory Synthesis Model that Resists Social Relationship Privacy AttacksACM Transactions on Intelligent Systems and Technology10.1145/349516013:3(1-28)Online publication date: 11-May-2022
https://dl.acm.org/doi/10.1145/3495160
Jin FHua WFrancia MChao POrlowska MZhou X(2022)A Survey and Experimental Study on Privacy-Preserving Trajectory Data PublishingIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2022.3174204(1-1)Online publication date: 2022
https://doi.org/10.1109/TKDE.2022.3174204
Jin FHua WRuan BZhou X(2022)Frequency-based Randomization for Guaranteeing Differential Privacy in Spatial Trajectories2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00175(1727-1739)Online publication date: May-2022
https://doi.org/10.1109/ICDE53745.2022.00175
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten