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dc.contributor.authorYiu, Man Lung
dc.contributor.authorAssent, Ira
dc.contributor.authorJensen, Christian S.
dc.contributor.authorKalnis,Panos
dc.date.accessioned2015-08-03T09:44:01Z
dc.date.available2015-08-03T09:44:01Z
dc.date.issued2012-02
dc.identifier.citationYiu, M. L., Assent, I., Jensen, C. S., & Kalnis, P. (2012). Outsourced Similarity Search on Metric Data Assets. IEEE Transactions on Knowledge and Data Engineering, 24(2), 338–352. doi:10.1109/tkde.2010.222
dc.identifier.issn1041-4347
dc.identifier.doi10.1109/TKDE.2010.222
dc.identifier.urihttp://hdl.handle.net/10754/562069
dc.description.abstractThis paper considers a cloud computing setting in which similarity querying of metric data is outsourced to a service provider. The data is to be revealed only to trusted users, not to the service provider or anyone else. Users query the server for the most similar data objects to a query example. Outsourcing offers the data owner scalability and a low-initial investment. The need for privacy may be due to the data being sensitive (e.g., in medicine), valuable (e.g., in astronomy), or otherwise confidential. Given this setting, the paper presents techniques that transform the data prior to supplying it to the service provider for similarity queries on the transformed data. Our techniques provide interesting trade-offs between query cost and accuracy. They are then further extended to offer an intuitive privacy guarantee. Empirical studies with real data demonstrate that the techniques are capable of offering privacy while enabling efficient and accurate processing of similarity queries.
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.urlhttp://ieeexplore.ieee.org/document/5620912/
dc.relation.urlhttp://www4.comp.polyu.edu.hk/%7Ecsmlyiu/journal/TKDE_metricpriv.pdf
dc.rights(c) 2012 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.
dc.rightsThis file is an open access version redistributed from: http://www4.comp.polyu.edu.hk/%7Ecsmlyiu/journal/TKDE_metricpriv.pdf
dc.subjectQuery processing
dc.subjectSecurity
dc.subjectintegrity
dc.subjectand protection.
dc.titleOutsourced similarity search on metric data assets
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.identifier.journalIEEE Transactions on Knowledge and Data Engineering
dc.identifier.wosutWOS:000298381000012
dc.eprint.versionPre-print
dc.contributor.institutionDepartment of Computing, Hong Kong Polytechnic University, Hung Hom, Hong Kong
dc.contributor.institutionDepartment of Computer Science, Aarhus University, Aarhus DK-8200, Denmark
dc.identifier.volume24
dc.identifier.issue2
dc.identifier.pages338-352
kaust.personKalnis, Panos
dc.identifier.eid2-s2.0-84555206093
refterms.dateFOA2021-04-27T10:52:16Z


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