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Paper: Must the Communication Graph of MPC Protocols be an Expander?

Authors:
Elette Boyle
Ran Cohen
Deepesh Data
Pavel Hubáček
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DOI: 10.1007/978-3-319-96878-0_9
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Conference: CRYPTO 2018
Abstract: Secure multiparty computation (MPC) on incomplete communication networks has been studied within two primary models: (1) Where a partial network is fixed a priori, and thus corruptions can occur dependent on its structure, and (2) Where edges in the communication graph are determined dynamically as part of the protocol. Whereas a rich literature has succeeded in mapping out the feasibility and limitations of graph structures supporting secure computation in the fixed-graph model (including strong classical lower bounds), these bounds do not apply in the latter dynamic-graph setting, which has recently seen exciting new results, but remains relatively unexplored.In this work, we initiate a similar foundational study of MPC within the dynamic-graph model. As a first step, we investigate the property of graph expansion. All existing protocols (implicitly or explicitly) yield communication graphs which are expanders, but it is not clear whether this is inherent. Our results consist of two types:Upper bounds: We demonstrate secure protocols whose induced communication graphs are not expanders, within a wide range of settings (computational, information theoretic, with low locality, and adaptive security), each assuming some form of input-independent setup.Lower bounds: In the setting without setup and adaptive corruptions, we demonstrate that for certain functionalities, no protocol can maintain a non-expanding communication graph against all adversarial strategies. Our lower bound relies only on protocol correctness (not privacy), and requires a surprisingly delicate argument.
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BibTeX
@inproceedings{crypto-2018-28813,
  title={Must the Communication Graph of MPC Protocols be an Expander?},
  booktitle={Advances in Cryptology – CRYPTO 2018},
  series={Lecture Notes in Computer Science},
  publisher={Springer},
  volume={10993},
  pages={243-272},
  doi={10.1007/978-3-319-96878-0_9},
  author={Elette Boyle and Ran Cohen and Deepesh Data and Pavel Hubáček},
  year=2018
}