SUGAR: SecUre GrAph QueRy Services*
[Abstract]
Graphs are powerful
tools for a wide range of real applications, from biological and chemical
databases, social networks, citation networks to information
networks. Large graph data repositories have been consistently found in recent
applications. Due to the high complexity of graph queries, e.g., subgraph
query, and the lack of IT expertise, hosting efficient graph query services for
the owners of graph data has been a technically challenging task. And hence,
they may prefer to outsource their services to third-party service providers
(SPs) for scalability, elasticity and performance.
Unfortunately, SPs may
not always be trusted. Security, typically the confidentiality and integrity
of the data, has been recognized as one of the critical attributes of Quality
of Services (QoS). This directly influences the
willingness of both data owners and query clients to use SP's services. To
address these concerns, this project proposes techniques to support
privacy-preserving and authenticated graph query services, respectively.
Confidentiality [1, 2, 4, 5]:
To protect the privacy of query graphs and/or data graphs, specifically the
topological structure (i.e., the adjacency matrices) of the graphs, this
project proposes efficient privacy-preserving subgraph isomorphism query and
reachability query. In particular, novel encryption schemes and algorithms were
carefully designed by adopting classical cryptographic schemes and seminal
query evaluation algorithms. Optimization strategies have been proposed to
enhance performance. Moreover, the privacy analysis shows the security
guarantees. Our experimental results show that the proposed techniques are
efficient and the optimizations are effective.
Data Integrity [3, 6]: To ensure data
integrity, this project proposes efficient authenticated subgraph isomorphism
and similarity queries, to guarantee the correctness (soundness and the
completeness) of query answers. Specifically, the project proposes several
novel methods derived from classical verifiable data structures, in particular,
Merkle Hash Tree (MHT). Several indexing techniques
and properties are proposed to optimize authentication performance. Theoretical
analysis and experiments show that the proposed algorithms guarantee data
integrity and return the query answers correctly and efficiently.
[Relevant US Patent]
[Relevant Publications]
[Implementation]
* This project is
supported by the following grants:
Adaptive Filtering for Efficient
Subgraph Isomorphism in Graph Databases
General Research Funds (GRF),
HKBU210510
Trusted Subgraph Similarity Query
Services
Faculty Research Grant FRG2/12-13/079
Structure-preserving
Subgraph Query Services
Faculty
Research Grant FRG2/13-14/073
For further information, please contact Zhe Fan, Byron Choi, Sourav S Bhowmick or Jianliang Xu.
Created on 17th March 2015.