Enabling search services on outsourced private spatial data

Handle URI:
http://hdl.handle.net/10754/561477
Title:
Enabling search services on outsourced private spatial data
Authors:
Yiu, Man Lung; Ghinita, Gabriel; Jensen, Christian Søndergaard; Kalnis, Panos ( 0000-0002-5060-1360 )
Abstract:
Cloud computing services enable organizations and individuals to outsource the management of their data to a service provider in order to save on hardware investments and reduce maintenance costs. Only authorized users are allowed to access the data. Nobody else, including the service provider, should be able to view the data. For instance, a real-estate company that owns a large database of properties wants to allow its paying customers to query for houses according to location. On the other hand, the untrusted service provider should not be able to learn the property locations and, e. g., selling the information to a competitor. To tackle the problem, we propose to transform the location datasets before uploading them to the service provider. The paper develops a spatial transformation that re-distributes the locations in space, and it also proposes a cryptographic-based transformation. The data owner selects the transformation key and shares it with authorized users. Without the key, it is infeasible to reconstruct the original data points from the transformed points. The proposed transformations present distinct trade-offs between query efficiency and data confidentiality. In addition, we describe attack models for studying the security properties of the transformations. Empirical studies demonstrate that the proposed methods are efficient and applicable in practice. © 2009 Springer-Verlag.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Computer Science Program
Publisher:
Springer Nature
Journal:
The VLDB Journal
Issue Date:
30-Oct-2009
DOI:
10.1007/s00778-009-0169-7
Type:
Article
ISSN:
10668888
Appears in Collections:
Articles; Computer Science Program; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorYiu, Man Lungen
dc.contributor.authorGhinita, Gabrielen
dc.contributor.authorJensen, Christian Søndergaarden
dc.contributor.authorKalnis, Panosen
dc.date.accessioned2015-08-02T09:12:21Zen
dc.date.available2015-08-02T09:12:21Zen
dc.date.issued2009-10-30en
dc.identifier.issn10668888en
dc.identifier.doi10.1007/s00778-009-0169-7en
dc.identifier.urihttp://hdl.handle.net/10754/561477en
dc.description.abstractCloud computing services enable organizations and individuals to outsource the management of their data to a service provider in order to save on hardware investments and reduce maintenance costs. Only authorized users are allowed to access the data. Nobody else, including the service provider, should be able to view the data. For instance, a real-estate company that owns a large database of properties wants to allow its paying customers to query for houses according to location. On the other hand, the untrusted service provider should not be able to learn the property locations and, e. g., selling the information to a competitor. To tackle the problem, we propose to transform the location datasets before uploading them to the service provider. The paper develops a spatial transformation that re-distributes the locations in space, and it also proposes a cryptographic-based transformation. The data owner selects the transformation key and shares it with authorized users. Without the key, it is infeasible to reconstruct the original data points from the transformed points. The proposed transformations present distinct trade-offs between query efficiency and data confidentiality. In addition, we describe attack models for studying the security properties of the transformations. Empirical studies demonstrate that the proposed methods are efficient and applicable in practice. © 2009 Springer-Verlag.en
dc.publisherSpringer Natureen
dc.subjectData outsourcingen
dc.subjectSpatial query processingen
dc.titleEnabling search services on outsourced private spatial dataen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.contributor.departmentComputer Science Programen
dc.identifier.journalThe VLDB Journalen
dc.contributor.institutionDepartment of Computing, Hong Kong Polytechnic University, Hong Kong, Chinaen
dc.contributor.institutionDepartment of Computer Science, Purdue University, West Lafayette, IN, United Statesen
dc.contributor.institutionDepartment of Computer Science, Aalborg University, Aalborg, Denmarken
kaust.authorKalnis, Panosen
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