SecGraph: Towards SGX-based Efficient and Confidentiality-Preserving Graph Search
arxiv(2024)
摘要
Graphs have more expressive power and are widely researched in various search
demand scenarios, compared with traditional relational and XML models. Today,
many graph search services have been deployed on a third-party server, which
can alleviate users from the burdens of maintaining large-scale graphs and huge
computation costs. Nevertheless, outsourcing graph search services to the
third-party server may invade users' privacy. PeGraph was recently proposed to
achieve the encrypted search over the social graph. The main idea of PeGraph is
to maintain two data structures XSet and TSet motivated by the OXT technology
to support encrypted conductive search. However, PeGraph still has some
limitations. First, PeGraph suffers from high communication and computation
costs in search operations. Second, PeGraph cannot support encrypted search
over dynamic graphs. In this paper, we propose an SGX-based efficient and
confidentiality-preserving graph search scheme SecGraph that can support
insertion and deletion operations. We first design a new proxy-token generation
method to reduce the communication cost. Then, we design an LDCF-encoded XSet
based on the Logarithmic Dynamic Cuckoo Filter to reduce the computation cost.
Finally, we design a new dynamic version of TSet named Twin-TSet to enable
encrypted search over dynamic graphs. We have demonstrated the confidentiality
preservation property of SecGraph through rigorous security analysis.
Experiment results show that SecGraph yields up to 208x improvement in search
time compared with PeGraph and the communication cost in PeGraph is up to 540x
larger than that in SecGraph.
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