Publication Type

Conference Proceeding Article

Publication Date

8-2012

Abstract

Shortest path computation is one of the most common queries in location-based services (LBSs). Although particularly useful, such queries raise serious privacy concerns. Exposing to a (potentially untrusted) LBS the client’s position and her destination may reveal personal information, such as social habits, health condition, shopping preferences, lifestyle choices, etc. The only existing method for privacy-preserving shortest path computation follows the obfuscation paradigm; it prevents the LBS from inferring the source and destination of the query with a probability higher than a threshold. This implies, however, that the LBS still deduces some information (albeit not exact) about the client’s location and her destination. In this paper we aim at strong privacy, where the adversary learns nothing about the shortest path query. We achieve this via established PIR techniques, which we treat as black-box building blocks. Experiments on real, large-scale road networks verify the efficiency and practicality of our schemes.

Keywords

Black boxes, Building blockes, Health condition, Information leakage, Lifestyle choices, Personal information, Privacy concerns, Privacy preserving, Private information retrieval, Road network, Shortest path, Shortest path computations

Discipline

Databases and Information Systems | Numerical Analysis and Scientific Computing

Research Areas

Data Management and Analytics

Publication

Proceedings of the VLDB Endowment: 38th VLDB 2012, August 27-31, Istanbul, Turkey

Volume

5

First Page

692

Last Page

703

Identifier

10.14778/2212351.2212352

Publisher

VLDB Endowment

City or Country

New York

Copyright Owner and License

LARC

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://dx.doi.org/10.14778/2212351.2212352

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