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Protecting location privacy against inference attacks

Authors:

Kazuhiro Minami,

Nikita BorisovAuthors Info & Claims

WPES '10: Proceedings of the 9th annual ACM workshop on Privacy in the electronic society

Pages 123 - 126

https://doi.org/10.1145/1866919.1866938

Published: 04 October 2010 Publication History

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Abstract

GPS-enabled mobile devices are a quickly growing market and users are starting to share their location information with each other through services such as Google Latitude. Location information, however, is very privacy-sensitive, since it can be used to infer activities, preferences, relationships, and other personal information, and thus access to it must be carefully protected. The situation is complicated by the possibility of inferring a users' location information from previous (or even future) movements. We argue that such inference means that traditional access control models that make a binary decision on whether a piece of information is released or not are not sufficient, and new policies must be designed that ensure that private information is not revealed either directly or through inference. We provide a formal definition of location privacy that incorporates an adversary's ability to predict location and discuss possible implementation of access control mechanisms that satisfy this definition. To support our reasoning, we analyze a preliminary data set to evaluate the accuracy of location prediction.

References

[1]

}}Denise Anthony, Tristan Henderson, and David Kotz. Privacy in location-aware computing environments. IEEE Pervasive Computing, 6(4):64--72, 2007.

Digital Library

Google Scholar

[2]

}}Richard Chow and Philippe Golle. Faking contextual data for fun, profit, and privacy. In Proceedings of the 8th ACM Workshop on Privacy in the Electronic Society (WPES), pages 105--108, New York, NY, USA, 2009. ACM.

Digital Library

Google Scholar

[3]

}}Jon Froehlich and John Krumm. Route prediction from trip observations. In Society of Automotive Engineers (SAE) 2008 World Congress, April 2008.

Crossref

Google Scholar

[4]

}}Glympse. http://www.glympse.com.

Google Scholar

[5]

}}Google latitude. http://www.google.com/latitude.

Google Scholar

[6]

}}Urs Hengartner and Peter Steenkiste. Access control to people location information. ACM Transactions on Information and System Security (TISSEC), 8(4):424--456, 2005.

Digital Library

Google Scholar

[7]

}}Instamapper. http://www.instamapper.com.

Google Scholar

[8]

}}Apu Kapadia, Tristan Henderson, Jeffrey J. Fielding, and David Kotz. Virtual Walls: Protecting Digital Privacy in Pervasive Environments. In Proceedings of the Fifth International Conference on Pervasive Computing (Pervasive), volume 4480 of LNCS, pages 162--179. Springer-Verlag, May 2007.

Digital Library

Google Scholar

[9]

}}John Krumm. Realistic Driving Trips For Location Privacy. In Pervasive Computing, number 5538 in Lecture Notes In Computer Science. Springer, 2009.

Digital Library

Google Scholar

[10]

}}John Krumm. A survey of computational location privacy. Personal and Ubiquitous Computing, 13(6):391--399, 2009.

Digital Library

Google Scholar

[11]

}}John Krumm and Eric Horvitz. Predestination: Inferring destinations from partial trajectories. In Proceedings of the 8th International Conference on Ubiquitous Computing (Ubicomp), pages 243--260, September 2006.

Digital Library

Google Scholar

[12]

}}Ginger Myles, Adrian Friday, and Nigel Davies. Preserving privacy in environments with location-based applications. IEEE Pervasive Computing, 2(1):56--64, January-March 2003.

Digital Library

Google Scholar

[13]

}}Libo Song, David Kotz, Ravi Jain, and Xiaoning He. Evaluating next cell predictors with extensive Wi-Fi mobility data. IEEE Transactions on Mobile Computing, 5(12):1633--1649, December 2006.

Digital Library

Google Scholar

[14]

}}How to tweet with your location. http://twitter.zendesk.com/entries/122236.

Google Scholar

Cited By

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Rasheed HMd Noor RAbdul Ghani NAhmad I(2024)Preserving location‐query privacy in location‐based services: A reviewSECURITY AND PRIVACY10.1002/spy2.412Online publication date: 15-May-2024
https://doi.org/10.1002/spy2.412
Alharthi RBanihani AAlzahrani AAlshehri AAlshahrani HFu HLiu AZhu Y(2018)Location Privacy Challenges in Spatial Crowdsourcing2018 IEEE International Conference on Electro/Information Technology (EIT)10.1109/EIT.2018.8500311(0564-0569)Online publication date: May-2018
https://doi.org/10.1109/EIT.2018.8500311
Liu BZhou WZhu TGao LXiang Y(2018)Location Privacy and Its Applications: A Systematic StudyIEEE Access10.1109/ACCESS.2018.28222606(17606-17624)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2822260
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Protecting location privacy against inference attacks

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Published In

WPES '10: Proceedings of the 9th annual ACM workshop on Privacy in the electronic society

October 2010

136 pages

ISBN:9781450300964

DOI:10.1145/1866919

General Chair:
Ehab Al-Shaer
University of North Carolina, Charlotte, USA
,
Program Chair:
Keith Frikken
Miami University, USA

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 04 October 2010

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CCS '10

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SIGSAC

CCS '10: 17th ACM Conference on Computer and Communications Security 2010

October 4, 2010

Illinois, Chicago, USA

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Overall Acceptance Rate 106 of 355 submissions, 30%

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Cited By

View all

Rasheed HMd Noor RAbdul Ghani NAhmad I(2024)Preserving location‐query privacy in location‐based services: A reviewSECURITY AND PRIVACY10.1002/spy2.412Online publication date: 15-May-2024
https://doi.org/10.1002/spy2.412
Alharthi RBanihani AAlzahrani AAlshehri AAlshahrani HFu HLiu AZhu Y(2018)Location Privacy Challenges in Spatial Crowdsourcing2018 IEEE International Conference on Electro/Information Technology (EIT)10.1109/EIT.2018.8500311(0564-0569)Online publication date: May-2018
https://doi.org/10.1109/EIT.2018.8500311
Liu BZhou WZhu TGao LXiang Y(2018)Location Privacy and Its Applications: A Systematic StudyIEEE Access10.1109/ACCESS.2018.28222606(17606-17624)Online publication date: 2018
https://doi.org/10.1109/ACCESS.2018.2822260
Wang SHsiu MTsai YTing IHong T(2017)Analysis of privacy and utility tradeoffs in anonymized mobile context streamsIntelligent Data Analysis10.3233/IDA-17087021:S1(S21-S39)Online publication date: 1-Jan-2017
https://dl.acm.org/doi/10.3233/IDA-170870
Murakami T(2017)Expectation-Maximization Tensor Factorization for Practical Location Privacy AttacksProceedings on Privacy Enhancing Technologies10.1515/popets-2017-00422017:4(138-155)Online publication date: 10-Oct-2017
https://doi.org/10.1515/popets-2017-0042
Agadakos IPolakis JPortokalidis GChoudhury TKo SCampbell AGanesan D(2017)TechuProceedings of the 15th Annual International Conference on Mobile Systems, Applications, and Services10.1145/3081333.3081345(475-487)Online publication date: 16-Jun-2017
https://dl.acm.org/doi/10.1145/3081333.3081345
Argyros GPetsios TSivakorn SKeromytis APolakis J(2017)Evaluating the Privacy Guarantees of Location Proximity ServicesACM Transactions on Privacy and Security10.1145/300720919:4(1-31)Online publication date: 3-Feb-2017
https://dl.acm.org/doi/10.1145/3007209
(2016)Localization Attacks Using Matrix and Tensor FactorizationIEEE Transactions on Information Forensics and Security10.1109/TIFS.2016.254786511:8(1647-1660)Online publication date: 1-Aug-2016
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Wang SHsiu MTing IHong T(2015)Toward Analyzing Privacy and Utility of Mobile User DataProceedings of the ASE BigData & SocialInformatics 201510.1145/2818869.2818909(1-6)Online publication date: 7-Oct-2015
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Polakis IArgyros GPetsios TSivakorn SKeromytis ARay ILi NKruegel C(2015)Where's Wally?Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security10.1145/2810103.2813605(817-828)Online publication date: 12-Oct-2015
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Protecting location privacy: optimal strategy against localization attacks

Protecting location privacy using location semantics