Article

MOBIHIDE: a mobilea peer-to-peer system for anonymous location-based queries

Authors:

Gabriel Ghinita,

Spiros SkiadopoulosAuthors Info & Claims

SSTD'07: Proceedings of the 10th international conference on Advances in spatial and temporal databases

Pages 221 - 238

Published: 16 July 2007 Publication History

Abstract

Modern mobile phones and PDAs are equipped with positioning capabilities (e.g., GPS). Users can access public location-based services (e.g., Google Maps) and ask spatial queries. Although communication is encrypted, privacy and confidentiality remain major concerns, since the queries may disclose the location and identity of the user. Commonly, spatial K-anonymity is employed to hide the query initiator among a group of K users. However, existing work either fails to guarantee privacy, or exhibits unacceptably long response time.

In this paper we propose MobiHide, a Peer-to-Peer system for anonymous location-based queries, which addresses these problems. MobiHide employs the Hilbert space-filling curve to map the 2-D locations of mobile users to 1-D space. The transformed locations are indexed by a Chord-based distributed hash table, which is formed by the mobile devices. The resulting Peer-to-Peer system is used to anonymize a query by mapping it to a random group of K users that are consecutive in the 1-D space. Compared to existing state-of-the-art, MobiHide does not provide theoretical anonymity guarantees for skewed query distributions. Nevertheless, it achieves strong anonymity in practice, and it eliminates system hotspots. Our experimental evaluation shows that MobiHide has good load balancing and fault tolerance properties, and is applicable to real-life scenarios with numerous mobile users.

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Cited By

Dai HLi HMeng XWang Y(2020)On the Vulnerability and Generality of K–Anonymity Location Privacy Under Continuous LBS RequestsWeb and Big Data10.1007/978-3-030-60290-1_28(351-359)Online publication date: 12-Aug-2020
https://dl.acm.org/doi/10.1007/978-3-030-60290-1_28
Li ZXing XSun GQian ZQian J(2020)Virtual Location Generation for Location Privacy Protection in VANETWireless Algorithms, Systems, and Applications10.1007/978-3-030-59019-2_6(49-58)Online publication date: 13-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-59019-2_6
Hashem TKulik LRamamohanarao KZhang RSoma S(2019)Protecting privacy for distance and rank based group nearest neighbor queriesWorld Wide Web10.1007/s11280-018-0570-522:1(375-416)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1007/s11280-018-0570-5
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Published In

cover image Guide Proceedings

SSTD'07: Proceedings of the 10th international conference on Advances in spatial and temporal databases

July 2007

478 pages

ISBN:9783540735397

Editors:
Dimitris Papadias
Hong Kong University of Science and Technology, Department of Computer Science and Engineering, Hong Kong, China
,
Donghui Zhang
Northeastern University, College of Computer & Information Science, Boston, MA
,
George Kollios
Boston University, Computer Science Department, Boston, MA

Sponsors

ESRI
Oracle Spatial
Microsoft Research: Microsoft Research

Publisher

Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 16 July 2007

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Cited By

Dai HLi HMeng XWang Y(2020)On the Vulnerability and Generality of K–Anonymity Location Privacy Under Continuous LBS RequestsWeb and Big Data10.1007/978-3-030-60290-1_28(351-359)Online publication date: 12-Aug-2020
https://dl.acm.org/doi/10.1007/978-3-030-60290-1_28
Li ZXing XSun GQian ZQian J(2020)Virtual Location Generation for Location Privacy Protection in VANETWireless Algorithms, Systems, and Applications10.1007/978-3-030-59019-2_6(49-58)Online publication date: 13-Sep-2020
https://dl.acm.org/doi/10.1007/978-3-030-59019-2_6
Hashem TKulik LRamamohanarao KZhang RSoma S(2019)Protecting privacy for distance and rank based group nearest neighbor queriesWorld Wide Web10.1007/s11280-018-0570-522:1(375-416)Online publication date: 1-Jan-2019
https://dl.acm.org/doi/10.1007/s11280-018-0570-5
Gupta RRao U(2019)VIC-PROWireless Personal Communications: An International Journal10.1007/s11277-019-06316-y107:2(1041-1059)Online publication date: 1-Jul-2019
https://dl.acm.org/doi/10.1007/s11277-019-06316-y
Jin HPapadimitratos PNoubir GConti MKasera S(2017)Resilient privacy protection for location-based services through decentralizationProceedings of the 10th ACM Conference on Security and Privacy in Wireless and Mobile Networks10.1145/3098243.3098268(253-258)Online publication date: 18-Jul-2017
https://dl.acm.org/doi/10.1145/3098243.3098268
Memon IArain Q(2017)Dynamic path privacy protection framework for continuous query service over road networksWorld Wide Web10.1007/s11280-016-0403-320:4(639-672)Online publication date: 1-Jul-2017
https://dl.acm.org/doi/10.1007/s11280-016-0403-3
Gupta RRao U(2017)An Exploration to Location Based Service and Its Privacy Preserving TechniquesWireless Personal Communications: An International Journal10.1007/s11277-017-4284-296:2(1973-2007)Online publication date: 1-Sep-2017
https://dl.acm.org/doi/10.1007/s11277-017-4284-2
Pournajaf LGarcia-Ulloa DXiong LSunderam V(2016)Participant Privacy in Mobile Crowd Sensing Task ManagementACM SIGMOD Record10.1145/2935694.293570044:4(23-34)Online publication date: 9-May-2016
https://dl.acm.org/doi/10.1145/2935694.2935700
Jadallah HAl Aghbari Z(2016)AmanProceedings of the International Conference on Internet of things and Cloud Computing10.1145/2896387.2896445(1-6)Online publication date: 22-Mar-2016
https://dl.acm.org/doi/10.1145/2896387.2896445
Guo MJin XPissinou NZanlongo SCarbunar BIyengar S(2015)In-Network Trajectory Privacy PreservationACM Computing Surveys10.1145/281818348:2(1-29)Online publication date: 12-Oct-2015
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