Asymmetric structure-preserving subgraph queries for large graphs

Zhe Fan, Koon Kau CHOI, Jianliang XU, Sourav S. Bhowmick

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

15 Citations (Scopus)


One fundamental type of query for graph databases is subgraph isomorphism queries (a.k.a subgraph queries). Due to the computational hardness of subgraph queries coupled with the cost of managing massive graph data, outsourcing the query computation to a third-party service provider has been an economical and scalable approach. However, confidentiality is known to be an important attribute of Quality of Service (QoS) in Query as a Service (QaaS). In this paper, we propose the first practical private approach for subgraph query services, asymmetric structure-preserving subgraph query processing, where the data graph is publicly known and the query structure/topology is kept secret. Unlike other previous methods for subgraph queries, this paper proposes a series of novel optimizations that only exploit graph structures, not the queries. Further, we propose a robust query encoding and adopt the novel cyclic group based encryption so that query processing is transformed into a series of private matrix operations. Our experiments confirm that our techniques are efficient and the optimizations are effective.

Original languageEnglish
Title of host publication2015 IEEE 31st International Conference on Data Engineering, ICDE 2015
PublisherIEEE Computer Society
Number of pages12
ISBN (Electronic)9781479979639
Publication statusPublished - 26 May 2015
Event31st IEEE International Conference on Data Engineering, ICDE 2015 - Seoul, Korea, Republic of
Duration: 13 Apr 201517 Apr 2015

Publication series

NameProceedings - International Conference on Data Engineering
ISSN (Print)1084-4627


Conference31st IEEE International Conference on Data Engineering, ICDE 2015
Country/TerritoryKorea, Republic of

Scopus Subject Areas

  • Software
  • Signal Processing
  • Information Systems


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