research-article

Protecting location privacy against spatial inferences: the PROBE approach

Authors:

Maria Luisa Damiani,

Claudio SilvestriAuthors Info & Claims

SPRINGL '09: Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS

Pages 32 - 41

https://doi.org/10.1145/1667502.1667511

Published: 03 November 2009 Publication History

Abstract

The widespread adoption of location-based services (LBS) raises increasing concerns for the protection of personal location information. A common strategy, referred to as obfuscation, to protect location privacy is based on forwarding the LSB provider a coarse user location instead of the actual user location. Conventional approaches, based on such technique, are however based only on geometric methods and therefore are unable to assure privacy when the adversary is aware of the geographical context. This paper provides a comprehensive solution to this problem. Our solution presents a novel approach that obfuscates the user location by taking into account the geographical context and user's privacy preferences. We define several theoretical notions underlying our approach. We then propose a strategy for generating obfuscated spaces and an efficient algorithm which implements such a strategy. The paper includes several experimental results assessing performance, storage requirements and accuracy for the approach. The paper also discusses the system architecture and shows that the approach can be deployed also for clients running on small devices.

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Cited By

Nowbakht PO'Sullivan LWall DHolloway P(2022)Implementation of novel polygon‐based obfuscation methods to improve privacy of agricultural dataTransactions in GIS10.1111/tgis.1300927:1(84-104)Online publication date: 30-Dec-2022
https://doi.org/10.1111/tgis.13009
Torrens P(2022)Data science for pedestrian and high street retailing as a framework for advancing urban informatics to individual scalesUrban Informatics10.1007/s44212-022-00009-x1:1Online publication date: 3-Oct-2022
https://doi.org/10.1007/s44212-022-00009-x
Naghizade EKulik LTanin EBailey J(2020)Privacy- and Context-aware Release of Trajectory DataACM Transactions on Spatial Algorithms and Systems10.1145/33634496:1(1-25)Online publication date: 30-Jan-2020
https://dl.acm.org/doi/10.1145/3363449
Show More Cited By

Index Terms

Protecting location privacy against spatial inferences: the PROBE approach
1. Information systems
  1. Data management systems
  2. Information systems applications

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Information & Contributors

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Published In

cover image ACM Conferences

SPRINGL '09: Proceedings of the 2nd SIGSPATIAL ACM GIS 2009 International Workshop on Security and Privacy in GIS and LBS

November 2009

79 pages

ISBN:9781605588537

DOI:10.1145/1667502

General Chair:
Elisa Bertino
Purdue University
,
Program Chairs:
Maria Luisa Damiani
University of Milan, Italy
,
Yücel Saygin
Sabanci University, Turkey

Copyright © 2009 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]

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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 03 November 2009

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GIS '09

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SIGSPATIAL

GIS '09: 17th SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 3, 2009

Washington, Seattle

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Citations

Cited By

Nowbakht PO'Sullivan LWall DHolloway P(2022)Implementation of novel polygon‐based obfuscation methods to improve privacy of agricultural dataTransactions in GIS10.1111/tgis.1300927:1(84-104)Online publication date: 30-Dec-2022
https://doi.org/10.1111/tgis.13009
Torrens P(2022)Data science for pedestrian and high street retailing as a framework for advancing urban informatics to individual scalesUrban Informatics10.1007/s44212-022-00009-x1:1Online publication date: 3-Oct-2022
https://doi.org/10.1007/s44212-022-00009-x
Naghizade EKulik LTanin EBailey J(2020)Privacy- and Context-aware Release of Trajectory DataACM Transactions on Spatial Algorithms and Systems10.1145/33634496:1(1-25)Online publication date: 30-Jan-2020
https://dl.acm.org/doi/10.1145/3363449
Alsubhi KAshraf MIlyas I(2020)HBLP: A Privacy Protection Framework for TIP Attributes in NTTP-Based LBS SystemsIEEE Access10.1109/ACCESS.2020.29856598(67718-67734)Online publication date: 2020
https://doi.org/10.1109/ACCESS.2020.2985659
Jain SKesswani N(2020)A Comparative Study of Location Privacy Preservation in the Internet of ThingsProcedia Computer Science10.1016/j.procs.2020.04.189171(1760-1769)Online publication date: 2020
https://doi.org/10.1016/j.procs.2020.04.189
Luo JYang MTsai K(2019)A geographic map-based middleware framework to obfuscate smart vehicles’ locationsMultimedia Tools and Applications10.1007/s11042-019-7350-9Online publication date: 15-Mar-2019
https://doi.org/10.1007/s11042-019-7350-9
Paturi AMazumdar S(2018)Can Spatial Transformation-Based Privacy Preservation Compromise Location Privacy?Trust, Privacy and Security in Digital Business10.1007/978-3-319-98385-1_6(69-84)Online publication date: 27-Jul-2018
https://doi.org/10.1007/978-3-319-98385-1_6
Xu MXu HXu C(2017)Personalized Semantic Location Privacy Preservation Algorithm Based on Query Processing Cost OptimizationSecurity, Privacy, and Anonymity in Computation, Communication, and Storage10.1007/978-3-319-72389-1_14(153-168)Online publication date: 7-Dec-2017
https://doi.org/10.1007/978-3-319-72389-1_14
Tang CCai C(2017)Verifiable mobile online social network privacy‐preserving location sharing schemeConcurrency and Computation: Practice and Experience10.1002/cpe.423829:24Online publication date: 14-Aug-2017
https://doi.org/10.1002/cpe.4238
Karlsson KWicker S(2016)The Effect of Location Granularity on Semantic Location InferencesProceedings of the 2016 49th Hawaii International Conference on System Sciences (HICSS)10.1109/HICSS.2016.276(2197-2204)Online publication date: 5-Jan-2016
https://dl.acm.org/doi/10.1109/HICSS.2016.276
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