Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/79623
DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Electronic and Information Engineering | en_US |
dc.creator | Xu, C | en_US |
dc.creator | Chen, Q | en_US |
dc.creator | Hu, HB | en_US |
dc.creator | Xu, JL | en_US |
dc.creator | Hei, XJ | en_US |
dc.date.accessioned | 2018-12-21T07:12:49Z | - |
dc.date.available | 2018-12-21T07:12:49Z | - |
dc.identifier.issn | 1041-4347 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/79623 | - |
dc.language.iso | en | en_US |
dc.publisher | Institute of Electrical and Electronics Engineers | en_US |
dc.rights | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, 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 component of this work in other works. | en_US |
dc.rights | The following publication C. Xu, Q. Chen, H. Hu, J. Xu and X. Hei, "Authenticating Aggregate Queries over Set-Valued Data with Confidentiality," in IEEE Transactions on Knowledge and Data Engineering, vol. 30, no. 4, pp. 630-644, 1 April 2018 is available at https://doi.org/10.1109/TKDE.2017.2773541. | en_US |
dc.subject | Query authentication | en_US |
dc.subject | Aggregate queries | en_US |
dc.subject | Set-valued data | en_US |
dc.subject | Merkle hash tree | en_US |
dc.title | Authenticating aggregate queries over set-valued data with confidentiality | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.spage | 630 | en_US |
dc.identifier.epage | 644 | en_US |
dc.identifier.volume | 30 | en_US |
dc.identifier.issue | 4 | en_US |
dc.identifier.doi | 10.1109/TKDE.2017.2773541 | en_US |
dcterms.abstract | With recent advances in data-as-a-service (DaaS) and cloud computing, aggregate query services over set-valued data are becoming widely available for business intelligence that drives decision making. However, as the service provider is often a third-party delegate of the data owner, the integrity of the query results cannot be guaranteed and is thus imperative to be authenticated. Unfortunately, existing query authentication techniques either do not work for set-valued data or they lack data confidentiality. In this paper, we propose authenticated aggregate queries over set-valued data that not only ensure the integrity of query results but also preserve the confidentiality of source data. As many aggregate queries are composed of multiset operations such as set union and subset, we first develop a family of privacy-preserving authentication protocols for primitive multiset operations. Using these protocols as building blocks, we present a privacy-preserving authentication framework for various aggregate queries and further optimize their authentication performance. Security analysis and empirical evaluation show that our proposed privacy-preserving authentication techniques are feasible and robust under a wide range of system workloads. | en_US |
dcterms.accessRights | open access | en_US |
dcterms.bibliographicCitation | IEEE transactions on knowledge and data engineering, 1 Apr. 2018, v. 30, no. 4, p. 630-644 | en_US |
dcterms.isPartOf | IEEE transactions on knowledge and data engineering | en_US |
dcterms.issued | 2018-04-01 | - |
dc.identifier.isi | WOS:000427192000002 | - |
dc.identifier.eissn | 1558-2191 | en_US |
dc.identifier.rosgroupid | 2017004568 | - |
dc.description.ros | 2017-2018 > Academic research: refereed > Publication in refereed journal | en_US |
dc.description.validate | 201812 bcrc | en_US |
dc.description.oa | Accepted Manuscript | en_US |
dc.identifier.FolderNumber | EIE-0557 | - |
dc.description.fundingSource | RGC | en_US |
dc.description.pubStatus | Published | en_US |
dc.identifier.OPUS | 6801262 | - |
Appears in Collections: | Journal/Magazine Article |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Authenticating_Aggregate_Queries.pdf | Pre-Published version | 1.48 MB | Adobe PDF | View/Open |
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