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Coding for Private and Secure Multiparty Computing

Yu, Qian and Raviv, Netanel and Avestimehr, A. Salman (2018) Coding for Private and Secure Multiparty Computing. In: 2018 IEEE Information Theory Workshop (ITW). IEEE , Piscataway, NJ, pp. 1-5. ISBN 978-1-5386-3599-5. http://resolver.caltech.edu/CaltechAUTHORS:20190205-074113118

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Abstract

We consider the problem of secure and private multiparty computation (MPC), in which the goal is to compute a general polynomial function distributedly over several workers, while keeping them oblivious to the content of the dataset, and preventing them from maliciously affecting the computation result. We demonstrate the role of Lagrange Coded Computing (LCC), a recently proposed coded computing technique that can be applied to general polynomial computations, on enabling secure and private MPC. We show that LCC offers both private and secure computation simultaneously, and is universal in the sense that all polynomials up to a certain degree can be computed on the same encoding. We also demonstrate that LCC achieves an optimal tradeoff between privacy and security, and requires a minimal amount of added randomness for privacy. Compared to prevalent algorithms in MPC (in particular the celebrated BGW scheme), we show that LCC significantly improves the storage, communication, and secret-sharing overhead needed for MPC.


Item Type:Book Section
Related URLs:
URLURL TypeDescription
https://doi.org/10.1109/ITW.2018.8613443DOIArticle
ORCID:
AuthorORCID
Raviv, Netanel0000-0002-1686-1994
Additional Information:© 2018 IEEE. This material is based upon work supported by Defense Advanced Research Projects Agency (DARPA) under Contract No. HR001117C0053. The views, opinions, and/or findings expressed are those of the author(s) and should not be interpreted as representing the official views or policies of the Department of Defense or the U.S. Government. This work is also supported by NSF Grants CCF-1763673 and CCF-1703575.
Funders:
Funding AgencyGrant Number
Defense Advanced Research Projects Agency (DARPA)HR001117C0053
NSFCCF-1763673
NSFCCF-1703575
Record Number:CaltechAUTHORS:20190205-074113118
Persistent URL:http://resolver.caltech.edu/CaltechAUTHORS:20190205-074113118
Official Citation:Q. Yu, N. Raviv and A. S. Avestimehr, "Coding for Private and Secure Multiparty Computing," 2018 IEEE Information Theory Workshop (ITW), Guangzhou, China, 2018, pp. 1-5. doi: 10.1109/ITW.2018.8613443
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:92646
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:05 Feb 2019 15:52
Last Modified:05 Feb 2019 15:52

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