Authenticating aggregate queries over set-valued data with confidentiality (extended abstract)

Cheng Xu, Qian Chen, Haibo HU, Jianliang XU, Xiaojun Hei

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1797-1798
Number of pages2
ISBN (Electronic)9781538655207
DOIs
Publication statusPublished - 24 Oct 2018
Event34th IEEE International Conference on Data Engineering, ICDE 2018 - Paris, France
Duration: 16 Apr 201819 Apr 2018

Publication series

NameProceedings - IEEE 34th International Conference on Data Engineering, ICDE 2018

Conference

Conference34th IEEE International Conference on Data Engineering, ICDE 2018
Country/TerritoryFrance
CityParis
Period16/04/1819/04/18

Scopus Subject Areas

  • Information Systems
  • Information Systems and Management
  • Hardware and Architecture

User-Defined Keywords

  • Aggregate Quereis
  • Merkel Hash Tree
  • Query Authentication
  • Set Valued Data

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