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ServeDB: Secure, verifiable, and efficient range queries on outsourced database

  • Songrui Wu
  • , Qi Li*
  • , Guoliang Li*
  • , Dong Yuan
  • , Xingliang Yuan
  • , Cong Wang
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

Data outsourcing to cloud has been a common IT practice nowadays due to its significant benefits. Meanwhile, security and privacy concerns are critical obstacles to hinder the further adoption of cloud. Although data encryption can mitigate the problem, it reduces the functionality of query processing, e.g., disabling SQL queries. Several schemes have been proposed to enable one-dimensional query on encrypted data, but multi-dimensional range query has not been well addressed. In this paper, we propose a secure and scalable scheme that can support multi-dimensional range queries over encrypted data. The proposed scheme has three salient features: (1) Privacy: the server cannot learn the contents of queries and data records during query processing. (2) Efficiency: we utilize hierarchical cubes to encode multi-dimensional data records and construct a secure tree index on top of such encoding to achieve sublinear query time. (3) Verifiability: our scheme allows users to verify the correctness and completeness of the query results to address server's malicious behaviors. We perform formal security analysis and comprehensive experimental evaluations. The results on real datasets demonstrate that our scheme achieves practical performance while guaranteeing data privacy and result integrity.
Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 35th International Conference on Data Engineering
Subtitle of host publicationICDE 2019
PublisherIEEE
Pages626-637
ISBN (Electronic)9781538674741
ISBN (Print)9781538674758
DOIs
Publication statusPublished - Apr 2019
Event35th IEEE International Conference on Data Engineering (ICDE 2019) - Parisian Macao, Macao, China
Duration: 8 Apr 201911 Apr 2019
http://conferences.cis.umac.mo/icde2019/?page_id=471

Publication series

NameProceedings - International Conference on Data Engineering
Volume2019-April
ISSN (Print)1063-6382
ISSN (Electronic)2375-026X

Conference

Conference35th IEEE International Conference on Data Engineering (ICDE 2019)
Abbreviated titleICDE 2019
PlaceMacao, China
Period8/04/1911/04/19
Internet address

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Research Keywords

  • Efficiency
  • Multi-dimensional range query
  • Privacy
  • Verifiability

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