GraphSE2: an encrypted graph database for privacy-preserving social search

Shangqi Lai, Xingliang Yuan, Shi-Feng Sun, Joseph K. Liu, Yuhong Liu, Dongxi Liu

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

for online social network services to address massive data breaches. GraphSE2 preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE2 provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE2 with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE2 is practical for querying a social graph with a million of users.

Original languageEnglish
Title of host publicationProceedings of the 2019 ACM Asia Conference on Computer and Communications Security
EditorsDieter Gollmann, Engin Kirda, Zhenkai Liang
Place of PublicationNew York NY USA
PublisherAssociation for Computing Machinery (ACM)
Pages41-54
Number of pages14
ISBN (Electronic)9781450367523
DOIs
Publication statusPublished - 2019
EventACM Symposium on Information, Computer and Communications Security 2019 - Auckland, New Zealand
Duration: 7 Jul 201912 Jul 2019
Conference number: 14th
https://asiaccs2019.blogs.auckland.ac.nz/

Conference

ConferenceACM Symposium on Information, Computer and Communications Security 2019
Abbreviated titleAsiaCCS 2019
CountryNew Zealand
CityAuckland
Period7/07/1912/07/19
Internet address

Keywords

  • Encrypted Query Processing
  • Graph Database
  • Social Search

Cite this

Lai, S., Yuan, X., Sun, S-F., Liu, J. K., Liu, Y., & Liu, D. (2019). GraphSE2: an encrypted graph database for privacy-preserving social search. In D. Gollmann, E. Kirda, & Z. Liang (Eds.), Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security (pp. 41-54). New York NY USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/3321705.3329803
Lai, Shangqi ; Yuan, Xingliang ; Sun, Shi-Feng ; Liu, Joseph K. ; Liu, Yuhong ; Liu, Dongxi. / GraphSE2 : an encrypted graph database for privacy-preserving social search. Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. editor / Dieter Gollmann ; Engin Kirda ; Zhenkai Liang. New York NY USA : Association for Computing Machinery (ACM), 2019. pp. 41-54
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title = "GraphSE2: an encrypted graph database for privacy-preserving social search",
abstract = "for online social network services to address massive data breaches. GraphSE2 preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE2 provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE2 with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE2 is practical for querying a social graph with a million of users.",
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author = "Shangqi Lai and Xingliang Yuan and Shi-Feng Sun and Liu, {Joseph K.} and Yuhong Liu and Dongxi Liu",
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Lai, S, Yuan, X, Sun, S-F, Liu, JK, Liu, Y & Liu, D 2019, GraphSE2: an encrypted graph database for privacy-preserving social search. in D Gollmann, E Kirda & Z Liang (eds), Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. Association for Computing Machinery (ACM), New York NY USA, pp. 41-54, ACM Symposium on Information, Computer and Communications Security 2019, Auckland, New Zealand, 7/07/19. https://doi.org/10.1145/3321705.3329803

GraphSE2 : an encrypted graph database for privacy-preserving social search. / Lai, Shangqi; Yuan, Xingliang; Sun, Shi-Feng; Liu, Joseph K.; Liu, Yuhong; Liu, Dongxi.

Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. ed. / Dieter Gollmann; Engin Kirda; Zhenkai Liang. New York NY USA : Association for Computing Machinery (ACM), 2019. p. 41-54.

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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AB - for online social network services to address massive data breaches. GraphSE2 preserves the functionality of social search, a key enabler for quality social network services, where social search queries are conducted on a large-scale social graph and meanwhile perform set and computational operations on user-generated contents. To enable efficient privacy-preserving social search, GraphSE2 provides an encrypted structural data model to facilitate parallel and encrypted graph data access. It is also designed to decompose complex social search queries into atomic operations and realise them via interchangeable protocols in a fast and scalable manner. We build GraphSE2 with various queries supported in the Facebook graph search engine and implement a full-fledged prototype. Extensive evaluations on Azure Cloud demonstrate that GraphSE2 is practical for querying a social graph with a million of users.

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Lai S, Yuan X, Sun S-F, Liu JK, Liu Y, Liu D. GraphSE2: an encrypted graph database for privacy-preserving social search. In Gollmann D, Kirda E, Liang Z, editors, Proceedings of the 2019 ACM Asia Conference on Computer and Communications Security. New York NY USA: Association for Computing Machinery (ACM). 2019. p. 41-54 https://doi.org/10.1145/3321705.3329803